Part 01-Module 04-Lesson 01_What Is Ahead/03. Rachel from Kaggle-uVsYYzxbyIg.mp4 27.7 MB
Part 15-Module 01-Lesson 06_Web Development/14. Bootstrap Library-KsrqjguHWUI.mp4 27.6 MB
Part 04-Module 01-Lesson 03_Gaussian Mixture Models and Cluster Validation/10. MLND - Unsupervised Learning - L3 10 Expectation Maximization Pt 2 MAIN V1 V2-B_xXd0mFUm4.mp4 27.6 MB
Part 17-Module 01-Lesson 01_Intro to Experiment Design and Recommendation Engines/03. Dan Frank Interview-Me-KRvZW1QQ.mp4 27.4 MB
Part 13-Module 01-Lesson 04_The Skills That Set You Apart/04. DSND T2 Intro Dan Frank V4-rTCPmVQDsEw.mp4 27.1 MB
Part 05-Module 01-Lesson 01_Congratulations!/04. Arvato Final Project-qBR6A0IQXEE.mp4 26.6 MB
Part 13-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree Program/03. Arvato Final Project-qBR6A0IQXEE.mp4 26.6 MB
Part 18-Module 01-Lesson 01_Data Scientist Capstone/06. Arvato Final Project-qBR6A0IQXEE.mp4 26.6 MB
Part 13-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree Program/03. Introduction to Blogging for Data Science-WrvGpRN5XQI.mp4 26.5 MB
Part 05-Module 01-Lesson 01_Congratulations!/04. Introduction to Blogging for Data Science-WrvGpRN5XQI.mp4 26.5 MB
Part 14-Module 01-Lesson 03_Project Write A Data Science Blog Post/01. Blogging for Data Science-WrvGpRN5XQI.mp4 26.5 MB
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/14. Interview with Art - Part 3-M6PKr3S1rPg.mp4 26.3 MB
Part 03-Module 01-Lesson 05_Deep Learning with PyTorch/10. Py Part 8 V1-3eqn5sgCOsY.mp4 26.1 MB
Part 14-Module 01-Lesson 01_The Data Science Process/13. How to Break Into the Field Solution-Db_2Lmwo4EY.mp4 25.7 MB
Part 06-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.mp4 24.9 MB
Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/04. MLND - Unsupervised Learning - L2 04 Examining SingleLink Clustering MAIN V1 V2-foLcmCOLDos.mp4 24.5 MB
Part 04-Module 01-Lesson 03_Gaussian Mixture Models and Cluster Validation/17. MLND - Unsupervised Learning - L3 18 External Validation Indices MAIN V1 V2-rXZM5X2-5D0.mp4 24.3 MB
Part 12-Module 01-Lesson 16_Logistic Regression/29. Model Diagnostics In Python-1Z4eorbfOOc.mp4 23.9 MB
Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/05. MLND - Unsupervised Learning - L2 05 CompleteLink AverageLink Ward MAIN V1 V2-dWGQVcZ95d0.mp4 23.6 MB
Part 12-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.mp4 23.1 MB
Part 12-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.mp4 23.0 MB
Part 14-Module 01-Lesson 01_The Data Science Process/40. Categorical Variables-p3gDUkBD9uM.mp4 22.9 MB
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/05. Interview with Art - Part 1-ClLYamtaO-Q.mp4 22.8 MB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/09. Recommendations 1 9 03362 V1-MwRSg5RASoc.mp4 21.1 MB
Part 11-Module 01-Lesson 04_Linear Transformation and Matrices/11. Linear Transformations 3-g_yTyRwMzXU.mp4 21.1 MB
Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/11. MLND - Unsupervised Learning - L2 08 DBSCAN MAIN V1 V2--dqyFkfnctI.mp4 20.9 MB
Part 06-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.mp4 20.9 MB
Part 04-Module 01-Lesson 03_Gaussian Mixture Models and Cluster Validation/11. MLND - Unsupervised Learning - L3 11 Visual Example Of EM Progress MAIN V1 V1-9x3d_eVJrJE.mp4 20.7 MB
Part 16-Module 01-Lesson 03_NLP Pipelines/04. Cleaning-qawXp9DPV6I.mp4 20.5 MB
Part 15-Module 01-Lesson 06_Web Development/30. Deployment-YPfNzpnm_Rk.mp4 20.3 MB
Part 06-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.mp4 19.9 MB
Part 17-Module 01-Lesson 01_Intro to Experiment Design and Recommendation Engines/04. Experimental Design Insights With Richard Sharp-XDBw2nfOrsU.mp4 19.8 MB
Part 17-Module 03-Lesson 02_Matrix Factorization for Recommendations/16. Recommendations 2 16 1051320 V1-_4N6h82szWo.mp4 19.8 MB
Part 01-Module 04-Lesson 01_What Is Ahead/02. Adam from IBM-NjjtY5UHyac.mp4 19.8 MB
Part 06-Module 01-Lesson 03_Control Flow/10. For Loops-UtX0PXSUCdY.mp4 19.3 MB
Part 12-Module 01-Lesson 15_Multiple Linear Regression/05. How Does MLR Work-bvM6eUYyurA.mp4 19.3 MB
Part 14-Module 01-Lesson 01_The Data Science Process/35. Imputation Methods-OwEWSBitF-Q.mp4 19.3 MB
Part 06-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.mp4 19.2 MB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/17. CNNs For Image Classification-l9vg_1YUlzg.mp4 19.0 MB
Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/03. MLND - Unsupervised Learning - L2 03 V2-pd9Ix3WMP_Q.mp4 19.0 MB
Part 12-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.mp4 18.9 MB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/06. Recommendations 1 6 11123244 V1-QlILlYuWF9U.mp4 18.8 MB
Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/15. MLND - Unsupervised Learning - L2 10 DBSCAN Examples Applications MAIN V1 V2-GhyFsjQ4FkA.mp4 18.6 MB
Part 15-Module 01-Lesson 07_Portfolio Exercise Deploy a Data Dashboard/08. Advanced API Code Walk-through-AkqO534YooE.mp4 18.6 MB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/02. Applications of CNNs-HrYNL_1SV2Y.mp4 18.6 MB
Part 14-Module 01-Lesson 01_The Data Science Process/32. Removing Data Part II-lPl6-Z098Rs.mp4 18.5 MB
Part 12-Module 01-Lesson 15_Multiple Linear Regression/17. Multicollinearity VIFs-wbtrXMusDe8.mp4 18.4 MB
Part 16-Module 03-Lesson 01_Strengthen Your Online Presence Using LinkedIn/01. Why Network-exjEm9Paszk.mp4 18.2 MB
Part 06-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.mp4 18.2 MB
Part 14-Module 01-Lesson 01_The Data Science Process/21. Predicting Salary-HTp4LA1MJh8.mp4 18.2 MB
Part 13-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree Program/02. Meet The Instructors-XAU2Nf51vfU.mp4 18.2 MB
Part 12-Module 01-Lesson 15_Multiple Linear Regression/22. Interactions Higher Order Terms-gMHwogzqPOk.mp4 18.1 MB
Part 07-Module 01-Lesson 03_SQL Aggregations/01. Introduction to Aggregations-5vRf_Ntoxfw.mp4 9.7 MB
Part 02-Module 01-Lesson 04_Decision Trees/14. Information Gain-k9iZL53PAmw.mp4 9.7 MB
Part 02-Module 01-Lesson 09_Training and Tuning/03. Model-Complexity-Graph Solution 2-5pWHGkNyRhA.mp4 9.7 MB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/15. Recommendations 1 14 10131720 V1-DWHYK0XSI70.mp4 9.7 MB
Part 04-Module 01-Lesson 05_Random Projection and ICA/01. L6 1 Random Projection MAIN V1 V1 V1-Iat1a8mzI-Y.mp4 9.6 MB
Part 02-Module 01-Lesson 07_Ensemble Methods/03. MLND SL DT 13 Random Forests MAIN V1-n5DhXhcYKcw.mp4 9.6 MB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/23. Visualizing CNNs-mnqS_EhEZVg.mp4 9.6 MB
Part 04-Module 01-Lesson 04_PCA/15. 14 Interpretation Solution V1-wU2duZa0ds0.mp4 9.6 MB
Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/09. MLND - Unsupervised Learning - L2 07 HC Examples Applications MAIN V1 V2-HTahFoQwk2g.mp4 9.6 MB
Part 16-Module 01-Lesson 01_Introduction to Data Engineering/02. Roles Of A Data Engineer-f57UbUlSDgo.mp4 9.6 MB
Part 13-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree Program/01. Welcome To DSND T2 V1 1 V1-ebJZrc2y85Q.mp4 9.5 MB
Part 12-Module 01-Lesson 04_Probability/15. One Of Three 1-bDCXSxkochE.mp4 9.5 MB
Part 06-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.mp4 9.5 MB
Part 04-Module 01-Lesson 01_Clustering/09. 10 KMeans In Scikit Learn V1-jkEgQLOcCGo.mp4 9.4 MB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/19. Recommendations 1 17b 36044330 V1-b5gFe8Ij-g0.mp4 9.4 MB
Part 16-Module 03-Lesson 01_Strengthen Your Online Presence Using LinkedIn/04. Pitching to a Recruiter-LxAdWaA-qTQ.mp4 9.4 MB
Part 07-Module 01-Lesson 03_SQL Aggregations/29. 11 CASE V2-BInXuTY_FzE.mp4 7.9 MB
Part 07-Module 01-Lesson 02_SQL Joins/14. Other JOINs-4edRxFmWUEw.mp4 7.9 MB
Part 12-Module 01-Lesson 03_Admissions Case Study/10. Gender Bias Revisited-dOa4Cl0wM0s.mp4 7.8 MB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/01. Adding Commits To A Repo - Intro-sLcOFQ4mGvo.mp4 7.8 MB
Part 12-Module 01-Lesson 16_Logistic Regression/09. Model Diagnostics-XsYFAtzF6e4.mp4 7.8 MB
Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/06. MLND - Unsupervised Learning - L2 06 Hierarchical Clustering Implementation MAIN V1 V1-tRqKsk5M9Mc.mp4 7.8 MB
Part 12-Module 01-Lesson 12_Hypothesis Testing/24. Conclusions In Hypothesis Testing-I0Mo7hcxahY.mp4 7.8 MB
Part 06-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.mp4 7.8 MB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/09. Programming Environment Setup-EKxDnCK0NAk.mp4 7.8 MB
Part 12-Module 01-Lesson 07_Bayes Rule/09. Equivalent Diagram-aUFWZ2uJuBE.mp4 7.7 MB
Part 06-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.mp4 7.7 MB
Part 14-Module 01-Lesson 01_The Data Science Process/30. Removing Data-97UTBiybYTs.mp4 7.7 MB
Part 12-Module 01-Lesson 12_Hypothesis Testing/28. Multiple Testing Corrections-DuMgeHrkIF0.mp4 7.7 MB
Part 12-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-1R44jvxIPJY.mp4 7.6 MB
Part 12-Module 01-Lesson 12_Hypothesis Testing/19. What Is A P-value Anyway-eU6pUZjqviA.mp4 7.6 MB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/18. Recommendations 1 17b 5451216 V1-lf2Q0AE5esk.mp4 7.6 MB
Part 02-Module 01-Lesson 05_Naive Bayes/05. SL NB 04 Bayes Theorem V1 V2-nVbPJmf53AI.mp4 7.6 MB
Part 12-Module 01-Lesson 09_Normal Distribution Theory/12. Normalizer-mQ_IjrtmmAk.mp4 7.6 MB
Part 20-Module 01-Lesson 01_Neural Networks/14. Error Functions-jfKShxGAbok.mp4 7.6 MB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/14. Error Functions-jfKShxGAbok.mp4 7.6 MB
Part 12-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-YIELbuet-ZE.mp4 7.5 MB
Part 17-Module 03-Lesson 02_Matrix Factorization for Recommendations/16. Recommendations 2 16 23242831 V1-WqNi0B_oRuA.mp4 7.5 MB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/10. Jupyter-qiYDWFLyXvg.mp4 7.5 MB
Part 08-Module 01-Lesson 02_Design of Visualizations/03. L2 031 Levels Of Measurement And Types Of Data V6-3Plhn5Q4xIA.mp4 7.4 MB
Part 02-Module 01-Lesson 06_Support Vector Machines/10. SVM 08 The C Parameter V2-6CxPhVo0hRw.mp4 7.4 MB
Part 16-Module 01-Lesson 04_Machine Learning Pipelines/09. 08 2 Advantages Of Using Pipelines V1 V2-eT1MS3n8fZ8.mp4 7.4 MB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/22. Recommendations 1 20 4271048 V1-2On65U7Panw.mp4 7.4 MB
Part 04-Module 01-Lesson 03_Gaussian Mixture Models and Cluster Validation/05. MLND - Unsupervised Learning - L3 05 Gaussian Distribution In 2D MAIN V1 V2-Ne-qRjO38qQ.mp4 7.3 MB
Part 12-Module 01-Lesson 12_Hypothesis Testing/29. How Do Confidence Intervals Hypothesis Tests Compare-KEmsEViOoMA.mp4 7.3 MB
Part 08-Module 01-Lesson 03_Univariate Exploration of Data/03. DataVis L3 03 V2-srRhFrSPdvs.mp4 7.3 MB
Part 06-Module 01-Lesson 07_Pandas/08. Pandas 4 V1-eMHUn9v9dds.mp4 7.3 MB
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/09. Writing READMEs with Walter-DQEfT2Zq5_o.mp4 7.3 MB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/10. More Personalized Recommendations-9l8mi7i6iW4.mp4 7.2 MB
Part 10-Module 01-Lesson 02_Create A Git Repo/01. Creating New Repositories - Intro-KT163BkqIeg.mp4 7.1 MB
Part 08-Module 01-Lesson 05_Multivariate Exploration of Data/02. DataVis L5C02 V3-bgDNMfG9Gfs.mp4 7.1 MB
Part 14-Module 01-Lesson 01_The Data Science Process/09. Business And Data Understanding - Part 2-iInjuIgBWIo.mp4 7.1 MB
Part 12-Module 01-Lesson 02_Descriptive Statistics - Part II/08. Standard Deviation Calculation-H5zA1A-XPoY.mp4 7.1 MB
Part 17-Module 02-Lesson 01_Concepts in Experiment Design/02. What Is An Experiment Pt 2-PYzN1usi7QY.mp4 7.1 MB
Part 12-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.mp4 7.0 MB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/02. Python Installation-2_P05aYChqQ.mp4 7.0 MB
Part 06-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.mp4 7.0 MB
Part 12-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.mp4 7.0 MB
Part 15-Module 01-Lesson 06_Web Development/24. Flask Pandas Plotly Part 1-xg7P8MnItdI.mp4 7.0 MB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/15. ROC Curve-2Iw5TiGzJI4.mp4 7.0 MB
Part 18-Module 01-Lesson 01_Data Scientist Capstone/09. Capstone-bq-H7M5BU3U.mp4 7.0 MB
Part 12-Module 01-Lesson 06_Conditional Probability/04. Medical Example 3-Iz4ViIg9ZlQ.mp4 6.9 MB
Part 06-Module 01-Lesson 06_NumPy/11. NumPy 6 V1-wtLRuGK0kW4.mp4 6.9 MB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/21. CrossEntropy V1-1BnhC6e0TFw.mp4 6.9 MB
Part 20-Module 01-Lesson 01_Neural Networks/21. CrossEntropy V1-1BnhC6e0TFw.mp4 6.9 MB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/01. Tagging, Branching, And Merging - Intro-sMf_r4_z-Ls.mp4 6.9 MB
Part 12-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-02v8ui9riew.mp4 6.9 MB
Part 02-Module 01-Lesson 09_Training and Tuning/01. 04 L Types Of Errors-Twf1qnPZeSY.mp4 6.9 MB
Part 14-Module 01-Lesson 01_The Data Science Process/18. It Is Not Always About ML-ECqflypBU7M.mp4 6.9 MB
Part 12-Module 01-Lesson 06_Conditional Probability/01. Introduction to Conditional Probability-Ok8948Wcbmo.mp4 6.9 MB
Part 12-Module 01-Lesson 02_Descriptive Statistics - Part II/11. Why the Standard Deviation-XlTBvjQ2t8w.mp4 6.9 MB
Part 20-Module 01-Lesson 02_Deep Neural Networks/06. Backpropagation V2-1SmY3TZTyUk.mp4 6.8 MB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/34. Backpropagation V2-1SmY3TZTyUk.mp4 6.8 MB
Part 15-Module 01-Lesson 04_Introduction to Object-Oriented Programming/03. L3 03 Class Obj Methods Attributes V1 1 V2-yvVMJt09HuA.mp4 6.8 MB
Part 08-Module 01-Lesson 02_Design of Visualizations/11. Design Integrity-y72_fVFtqlY.mp4 6.8 MB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/19. Recommendations 1 17b 31423505 V1-A0uOjClDnW8.mp4 6.8 MB
Part 02-Module 01-Lesson 10_Finding Donors Project/07. Project 1-PNsxDWtpQTk.mp4 6.7 MB
Part 03-Module 01-Lesson 03_Training Neural Networks/04. Underfitting And Overfitting-xj4PlXMsN-Y.mp4 6.7 MB
Part 04-Module 01-Lesson 03_Gaussian Mixture Models and Cluster Validation/08. MLND - Unsupervised Learning - L3 08 Overview Of The Expectation Maximization Algorithm MAIN V1 V1-XdQfFnnj5Xo.mp4 6.7 MB
Part 08-Module 01-Lesson 03_Univariate Exploration of Data/03. L3 031 Bar Charts V3-ybXcduB6cXA.mp4 6.7 MB
Part 02-Module 01-Lesson 01_Machine Learning Bird's Eye View/06. Deep Learning And Neural Networks-4rKw3ekE5Wk.mp4 6.7 MB
Part 17-Module 02-Lesson 01_Concepts in Experiment Design/01. Introduction-RVcFzwBXI2M.mp4 6.7 MB
Part 19-Module 01-Lesson 01_Congratulations!/01. Congrats-OTp4YOTDd0Q.mp4 6.7 MB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/18. Recommendations 1 17a 0422 V1-J4MOXJhMGGA.mp4 6.7 MB
Part 12-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.mp4 6.6 MB
Part 02-Module 01-Lesson 04_Decision Trees/04. Recommending Apps-nEvW8B1HNq4.mp4 6.6 MB
Part 12-Module 01-Lesson 13_Case Study AB tests/02. AB Testing-EcWvhbIjT9o.mp4 6.6 MB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/12. Types Of Collaborative Filtering-fZhkWHHP6SM.mp4 4.1 MB
Part 12-Module 01-Lesson 13_Case Study AB tests/07. Metric - Click Through Rate-EpfoKAwV_Eg.mp4 4.1 MB
Part 02-Module 01-Lesson 02_Linear Regression/01. Welcome To Linear Regression-zxZkTkM34BY.mp4 4.1 MB
Part 12-Module 01-Lesson 11_Confidence Intervals/11. Traditional vs. Bootstrapping Confidence Intervals-eZ8lyiumXDY.mp4 4.1 MB
Part 12-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.mp4 4.1 MB
Part 04-Module 01-Lesson 04_PCA/18. 17 PCA Recap V1-Egz3-noHCmg.mp4 4.1 MB
Part 07-Module 01-Lesson 03_SQL Aggregations/25. DATE Functions I-E7Z6GMFVmIY.mp4 4.0 MB
Part 08-Module 01-Lesson 03_Univariate Exploration of Data/01. L3 011 Intro V3-4BpAF4MYKm8.mp4 4.0 MB
Part 02-Module 01-Lesson 02_Linear Regression/13. Minimizing Error Functions-RbT2TXN_6tY.mp4 4.0 MB
Part 20-Module 01-Lesson 01_Neural Networks/05. Linear Boundaries-X-uMlsBi07k.mp4 4.0 MB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/05. Linear Boundaries-X-uMlsBi07k.mp4 4.0 MB
Part 02-Module 01-Lesson 03_Perceptron Algorithm/04. Linear Boundaries-X-uMlsBi07k.mp4 4.0 MB
Part 12-Module 01-Lesson 02_Descriptive Statistics - Part II/22. Outliers Advice-BhhDoTgYQmI.mp4 4.0 MB
Part 20-Module 01-Lesson 01_Neural Networks/18. Maximum Likelihood 2-6nUUeQ9AeUA.mp4 4.0 MB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/18. Maximum Likelihood 2-6nUUeQ9AeUA.mp4 4.0 MB
Part 02-Module 01-Lesson 01_Machine Learning Bird's Eye View/03. A Little More History - A Computer Scientist's Perspective-sVT9nX6HTyU.mp4 4.0 MB
Part 12-Module 01-Lesson 08_Python Probability Practice/02. Simulating Coin Flips-7YtQNZ3iy6o.mp4 4.0 MB
Part 16-Module 01-Lesson 02_ETL Pipelines/34. Scaling Data-OgjTk3XCUUE.mp4 4.0 MB
Part 07-Module 01-Lesson 03_SQL Aggregations/02. NULLs-WYUkLKn6XCw.mp4 4.0 MB
Part 07-Module 01-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.mp4 4.0 MB
Part 08-Module 01-Lesson 04_Bivariate Exploration of Data/13. L4 131 Line Plots V1-kSntEWPuOa0.mp4 4.0 MB
Part 12-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.mp4 4.0 MB
Part 16-Module 01-Lesson 03_NLP Pipelines/26. GloVe-KK3PMIiIn8o.mp4 4.0 MB
Part 12-Module 01-Lesson 01_Descriptive Statistics - Part I/08. Continuous vs. Discrete Data-BzgZebZD9kk.mp4 4.0 MB
Part 14-Module 01-Lesson 02_Communicating to Stakeholders/04. L3 Git And Github WalkThrough V1-buMNfXkj9fg.mp4 4.0 MB
Part 04-Module 01-Lesson 04_PCA/02. Lesson Topics-LBzA08F_r4w.mp4 4.0 MB
Part 07-Module 01-Lesson 06_[Advanced] SQL Window Functions/01. Introduction to Window Functions-u3qLjP8KMKc.mp4 4.0 MB
Part 06-Module 01-Lesson 07_Pandas/04. Pandas 1 V1-iXnYN8cnhzs.mp4 4.0 MB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/07. Outro-ot4fPX1jzOI.mp4 4.0 MB
Part 12-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.mp4 4.0 MB
Part 12-Module 01-Lesson 02_Descriptive Statistics - Part II/18. Data in the Real World-HmipezTjTDY.mp4 4.0 MB
Part 10-Module 01-Lesson 01_What is Version Control/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 30 Configure Terminal-CCYjHfBk9hw.mp4 4.0 MB
Part 06-Module 01-Lesson 07_Pandas/05. Pandas 2 V1-B7MuFIwboKU.mp4 4.0 MB
Part 14-Module 01-Lesson 01_The Data Science Process/19. The Data Science Process Modeling-bzR6HQBn5CA.mp4 3.9 MB
Part 20-Module 01-Lesson 01_Neural Networks/24. Gradient Descent-rhVIF-nigrY.mp4 3.9 MB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/24. Gradient Descent-rhVIF-nigrY.mp4 3.9 MB
Part 12-Module 01-Lesson 12_Hypothesis Testing/17. Simulating From the Null-sL2yJtHZd8Y.mp4 3.9 MB
Part 08-Module 01-Lesson 04_Bivariate Exploration of Data/03. Data Vis L4 C03 V1-0F6ldBC6Nbs.mp4 3.9 MB
Part 12-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.mp4 3.9 MB
Part 08-Module 01-Lesson 04_Bivariate Exploration of Data/13. Data Vis L4 C13 V1-Z7NjwA6jbjU.mp4 3.9 MB
Part 08-Module 01-Lesson 04_Bivariate Exploration of Data/09. Data Vis L4 C09 V1-OnzWhpgM9Vs.mp4 3.9 MB
Part 07-Module 01-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.mp4 3.8 MB
Part 08-Module 01-Lesson 03_Univariate Exploration of Data/15. L3 141 Lesson Summary V1-7ZaSMbsJUWU.mp4 3.8 MB
Part 10-Module 01-Lesson 01_What is Version Control/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 23 Configure Terminal-h00n9QLfbqU.mp4 3.8 MB
Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/12. MLND - Unsupervised Learning - L2 09 DBSCAN Implementation MAIN V1 V1-qEMUzQFylg8.mp4 3.8 MB
Part 12-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.mp4 3.8 MB
Part 07-Module 01-Lesson 05_SQL Data Cleaning/11. CAST-LbyOq4ofLng.mp4 3.8 MB
Part 10-Module 01-Lesson 07_Working With Remotes/07. Lesson Wrap Up-6Koa4nAu-04.mp4 3.0 MB
Part 12-Module 01-Lesson 01_Descriptive Statistics - Part I/04. What is Data-ldTDAjrVsA8.mp4 3.0 MB
Part 12-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.mp4 2.9 MB
Part 12-Module 01-Lesson 14_Regression/02. Introduction to Machine Learning-pLcFPPI1L-0.mp4 2.9 MB
Part 02-Module 01-Lesson 01_Machine Learning Bird's Eye View/04. Types Of Machine Learning - Supervised-Jn3xugBvs2U.mp4 2.9 MB
Part 08-Module 01-Lesson 07_Visualization Case Study/07. L7 0F1 Congrats V3-LF-obnL7CI0.mp4 2.9 MB
Part 12-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.mp4 2.9 MB
Part 12-Module 01-Lesson 11_Confidence Intervals/01. Confidence Intervals Introduction-crleT4000ak.mp4 2.9 MB
Part 15-Module 01-Lesson 03_Software Engineering Practices Pt II/05. 07 Unit Testing Tools V1-8bKhOyFbX_Y.mp4 2.9 MB
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/13. Participating in open source projects-OxL-gMTizUA.mp4 2.9 MB
Part 10-Module 01-Lesson 01_What is Version Control/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 11 Google Docs Revision History Walkthrough-GcvvbdKEchk.mp4 2.9 MB
Part 12-Module 01-Lesson 05_Binomial Distribution/13. Binomial 4-mvJUNYfHngY.mp4 2.9 MB
Part 12-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.mp4 2.9 MB
Part 14-Module 01-Lesson 02_Communicating to Stakeholders/10. Three Steps To Captivate Your Audience-BWS3oQYS-c4.mp4 2.9 MB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/01. 01 Intro-4C4PuJANIdE.mp4 2.9 MB
Part 12-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.mp4 2.9 MB
Part 08-Module 01-Lesson 05_Multivariate Exploration of Data/05. L5 051 Faceting In Two Directions V3-lz5dcoTcV2o.mp4 2.8 MB
Part 12-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-mFfbts1lAEo.mp4 2.8 MB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/09. AND And OR Perceptrons-45K5N0P9wJk.mp4 2.8 MB
Part 20-Module 01-Lesson 01_Neural Networks/08. AND And OR Perceptrons-45K5N0P9wJk.mp4 2.8 MB
Part 02-Module 01-Lesson 03_Perceptron Algorithm/07. AND And OR Perceptrons-45K5N0P9wJk.mp4 2.8 MB
Part 12-Module 01-Lesson 04_Probability/05. Loaded Coin 2-Y7tnbth-gag.mp4 824.8 kB
Part 12-Module 01-Lesson 06_Conditional Probability/08. Medical Example 7-cw_zgQbAWNU.mp4 823.0 kB
Part 12-Module 01-Lesson 04_Probability/03. Fair Coin-fSKL742j-zk.mp4 817.0 kB
Part 12-Module 01-Lesson 16_Logistic Regression/26. Practicing TP, FP, FN with Rumsfeld-dBax3E1AC2s.mp4 811.8 kB
Part 10-Module 01-Lesson 07_Working With Remotes/06. Pull Vs Fetch-kxXdk2HcOBo.mp4 806.8 kB
Part 12-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-T2dveKB64Ho.mp4 806.7 kB
Part 02-Module 01-Lesson 06_Support Vector Machines/img/screen-shot-2018-06-02-at-5.52.44-pm.png 804.6 kB
Part 12-Module 01-Lesson 16_Logistic Regression/22. Bush Precision and Recall-8fM13xqU2a8.mp4 793.6 kB
Part 12-Module 01-Lesson 09_Normal Distribution Theory/09. Maximum Value-rjpcSymYulE.mp4 790.4 kB
Part 12-Module 01-Lesson 16_Logistic Regression/10. Confusion Matrices-bEAaNv-CBQ4.mp4 789.1 kB
Part 12-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-r8stm2et_hI.mp4 784.0 kB
Part 01-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree program/img/get-hired-with-the-udacity-career-portal.gif 774.9 kB
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Part 12-Module 01-Lesson 07_Bayes Rule/12. Normalizer-W5i-gRAvZxs.mp4 772.6 kB
Part 16-Module 03-Lesson 01_Strengthen Your Online Presence Using LinkedIn/img/screen-shot-2018-02-23-at-5.00.25-pm.png 772.4 kB
Part 12-Module 01-Lesson 07_Bayes Rule/17. Disease Test 4-UERKMwmkAsM.mp4 771.1 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-udXhxyls5Dw.mp4 769.9 kB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/img/student-quiz.png 767.0 kB
Part 20-Module 01-Lesson 01_Neural Networks/img/student-quiz.png 767.0 kB
Part 02-Module 01-Lesson 03_Perceptron Algorithm/img/student-quiz.png 767.0 kB
Part 12-Module 01-Lesson 07_Bayes Rule/15. Disease Test 2-GsneDVJB75E.mp4 765.6 kB
Part 12-Module 01-Lesson 06_Conditional Probability/02. Medical Example 1-E1ph6NP3_v4.mp4 765.1 kB
Part 02-Module 01-Lesson 07_Ensemble Methods/img/decision-tree-sketch.png 762.7 kB
Part 12-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-2cUiqlbt-hc.mp4 737.8 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/08. Aggregation 2-xhpEqsHTf3g.mp4 736.7 kB
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/img/6509638772.gif 728.1 kB
Part 07-Module 01-Lesson 03_SQL Aggregations/09. MIN MAX-1ewVsgWUih8.mp4 710.3 kB
Part 02-Module 01-Lesson 02_Linear Regression/17. DLND REG 12 Absolute Vs Squared Error 2 V1 (1)-7El1OH17Oi4.mp4 709.4 kB
Part 12-Module 01-Lesson 07_Bayes Rule/07. Total Probability-_hXCgF-aMB0.mp4 688.4 kB
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Part 12-Module 01-Lesson 04_Probability/11. Two Flips 4-rRPwknIDuI0.mp4 679.3 kB
Part 12-Module 01-Lesson 09_Normal Distribution Theory/11. Minimum Value-LNzmJUj8K8w.mp4 677.0 kB
Part 02-Module 01-Lesson 02_Linear Regression/17. Absolute Vs Squared Error-csvdjaqt1GM.mp4 676.1 kB
Part 10-Module 01-Lesson 07_Working With Remotes/04. L1 - Git Push In Theory-21TvMEtMRys.mp4 671.9 kB
Part 12-Module 01-Lesson 07_Bayes Rule/06. Normalizing 3-etrUbOAoh1U.mp4 666.1 kB
Part 02-Module 01-Lesson 07_Ensemble Methods/img/screen-shot-2018-01-03-at-2.20.30-pm.png 662.9 kB
Part 12-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6-iyE5h48qPFQ.mp4 655.0 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-github-homepage-new-repo-button.png 647.8 kB
Part 02-Module 01-Lesson 09_Training and Tuning/img/models.png 643.0 kB
Part 12-Module 01-Lesson 15_Multiple Linear Regression/img/screen-shot-2017-12-07-at-9.43.05-am.png 632.9 kB
Part 12-Module 01-Lesson 15_Multiple Linear Regression/img/screen-shot-2017-12-07-at-1.33.46-pm.png 632.8 kB
Part 12-Module 01-Lesson 15_Multiple Linear Regression/img/screen-shot-2017-12-07-at-3.56.39-pm.png 625.1 kB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/img/and-to-or.png 620.7 kB
Part 02-Module 01-Lesson 03_Perceptron Algorithm/img/and-to-or.png 620.7 kB
Part 20-Module 01-Lesson 01_Neural Networks/img/and-to-or.png 620.7 kB
Part 12-Module 01-Lesson 07_Bayes Rule/12. Normalizer-G9yQ_URDrDQ.mp4 617.8 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-github-homepage.png 611.0 kB
Part 16-Module 03-Lesson 01_Strengthen Your Online Presence Using LinkedIn/img/profile-pics.jpg 609.9 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-merge-fast-forward.gif 609.7 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/media/conda_default_install.mp4 609.6 kB
Part 10-Module 01-Lesson 08_Working On Another Developer's Repository/img/ud456-l2-04-issue-comments.png 595.4 kB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/07. Accuracy 2-ueYCLfd_aNQ.mp4 587.6 kB
Part 11-Module 01-Lesson 01_Introduction/img/grant.png 583.6 kB
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-AF07y1oAim0.mp4 583.0 kB
Part 12-Module 01-Lesson 16_Logistic Regression/11. Confusion Matrix Practice 1-Nn_8kCRYn2k.mp4 582.7 kB
Part 12-Module 01-Lesson 16_Logistic Regression/16. How Many Schroeders-jO81hfubpXY.mp4 571.9 kB
Part 01-Module 02-Lesson 01_Get Help from Peers and Mentors/img/screen-shot-2018-11-07-at-9.59.16-pm.png 541.9 kB
Part 13-Module 01-Lesson 02_Get Help from Peers and Mentors/img/screen-shot-2018-11-07-at-9.59.16-pm.png 541.9 kB
Part 12-Module 01-Lesson 06_Conditional Probability/06. Medical Example 5-fqt7NIvMB0s.mp4 541.6 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/05. Admissions 4--GMhV1twy6Y.mp4 535.6 kB
Part 12-Module 01-Lesson 12_Hypothesis Testing/img/screen-shot-2018-11-19-at-11.32.05-am.png 533.6 kB
Part 10-Module 01-Lesson 09_Staying In Sync With A Remote Repository/img/ud456-l3-04-pull-request-comment.png 532.1 kB
Part 12-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-zB2Y-5YEIec.mp4 531.5 kB
Part 12-Module 01-Lesson 16_Logistic Regression/15. Confusion Matrix for Eigenfaces-jkjr_prWyt8.mp4 526.0 kB
Part 06-Module 01-Lesson 06_NumPy/img/screen-shot-2018-03-19-at-2.30.59-pm.png 519.6 kB
Part 06-Module 01-Lesson 01_Why Python Programming/img/screen-shot-2018-03-19-at-2.30.59-pm.png 519.6 kB
Part 06-Module 01-Lesson 07_Pandas/img/screen-shot-2018-03-19-at-2.30.59-pm.png 519.6 kB
Part 12-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-tIrqdYTT_9Q.mp4 518.2 kB
Part 10-Module 01-Lesson 08_Working On Another Developer's Repository/img/ud456-l2-04-lighthouse-issues.png 517.8 kB
Part 10-Module 01-Lesson 03_Review a Repo's History/img/ud123-l3-git-log-vs-git-log-oneline.png 516.7 kB
Part 12-Module 01-Lesson 16_Logistic Regression/24. False Positives in Eigenfaces-0bEbJ33dUis.mp4 514.1 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 54 Content On Different Branches-Px6EUylw8Uw.mp4 511.5 kB
Part 02-Module 01-Lesson 02_Linear Regression/img/house.png 503.3 kB
Part 10-Module 01-Lesson 03_Review a Repo's History/img/ud123-l3-project-in-editor.png 501.8 kB
Part 12-Module 01-Lesson 15_Multiple Linear Regression/img/screen-shot-2018-04-29-at-10.10.52-am.png 498.7 kB
Part 12-Module 01-Lesson 07_Bayes Rule/26. Robot Sensing 6-Se-ddM2Wdac.mp4 496.3 kB
Part 12-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-7ZLe_JP5wRY.mp4 491.1 kB
Part 12-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-goEMc0w58xM.mp4 484.7 kB
Part 03-Module 01-Lesson 03_Training Neural Networks/img/screen-shot-2018-03-19-at-3.49.28-pm.png 482.9 kB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/img/screen-shot-2018-03-19-at-3.49.28-pm.png 482.9 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-rDw0TIpwJ-c.mp4 478.6 kB
Part 02-Module 01-Lesson 06_Support Vector Machines/img/screen-shot-2018-06-02-at-6.07.54-pm.png 476.9 kB
assets/img/udacimak.png 472.1 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3030118734.gif 471.1 kB
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/img/6485174133.gif 469.1 kB
Part 10-Module 01-Lesson 08_Working On Another Developer's Repository/img/ud456-l2-04-new-issue-button.png 467.2 kB
Part 10-Module 01-Lesson 09_Staying In Sync With A Remote Repository/img/ud456-l3-03-watched-repos.png 461.7 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-8j5hria6Rc8.mp4 458.7 kB
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/img/6499079068.gif 456.6 kB
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/img/6551597473.gif 455.0 kB
Part 03-Module 01-Lesson 05_Deep Learning with PyTorch/img/screen-shot-2018-03-19-at-2.49.57-pm.png 453.1 kB
Part 08-Module 01-Lesson 03_Univariate Exploration of Data/img/tidy-data-three.png 448.1 kB
Part 13-Module 01-Lesson 02_Get Help from Peers and Mentors/img/image4.png 446.9 kB
Part 01-Module 02-Lesson 01_Get Help from Peers and Mentors/img/image4.png 446.9 kB
Part 10-Module 01-Lesson 09_Staying In Sync With A Remote Repository/img/ud456-l3-03-starred-repos.png 444.3 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/img/conda-search.png 441.2 kB
Part 12-Module 01-Lesson 07_Bayes Rule/16. Disease Test 3-PfEYA6z-19w.mp4 433.9 kB
index.html 432.5 kB
Part 12-Module 01-Lesson 16_Logistic Regression/25. False Negatives in Eigenfaces-dyShKWpTo-c.mp4 429.0 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3039578581.gif 426.6 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-project-github-no-commits.png 423.2 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-04-commit-count-remote.png 418.5 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3043028606.gif 418.0 kB
Part 10-Module 01-Lesson 03_Review a Repo's History/img/ud123-l3-git-log-vs-git-log-stat.png 414.0 kB
Part 08-Module 01-Lesson 03_Univariate Exploration of Data/img/tidy-data-four.png 407.4 kB
Part 20-Module 01-Lesson 02_Deep Neural Networks/20. Random Restart-idyBBCzXiqg.mp4 404.5 kB
Part 03-Module 01-Lesson 03_Training Neural Networks/10. Random Restart-idyBBCzXiqg.mp4 404.5 kB
Part 02-Module 01-Lesson 06_Support Vector Machines/img/screen-shot-2018-06-02-at-5.34.36-pm.png 404.1 kB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/img/or-quiz.png 403.1 kB
Part 02-Module 01-Lesson 03_Perceptron Algorithm/img/or-quiz.png 403.1 kB
Part 20-Module 01-Lesson 01_Neural Networks/img/or-quiz.png 403.1 kB
Part 12-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-4qW7a5E74No.mp4 400.3 kB
Part 08-Module 01-Lesson 03_Univariate Exploration of Data/img/tidy-data-one.png 399.7 kB
Part 10-Module 01-Lesson 01_What is Version Control/img/ud123-l1-google-docs-saving-progress.gif 399.4 kB
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/img/mat-leonard-circle.png 394.1 kB
Part 10-Module 01-Lesson 01_What is Version Control/img/ud123-l1-git-course-outline.png 387.5 kB
Part 13-Module 01-Lesson 03_Get Help with Your Account/img/screen-shot-2018-11-09-at-7.49.50-pm.png 384.6 kB
Part 01-Module 02-Lesson 02_Get Help with Your Account/img/screen-shot-2018-11-09-at-7.49.50-pm.png 384.6 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3021738574.gif 384.0 kB
Part 08-Module 01-Lesson 03_Univariate Exploration of Data/img/tidy-data-two.png 380.7 kB
Part 02-Module 01-Lesson 06_Support Vector Machines/img/margin-geometry-images.008.jpeg 378.3 kB
Part 13-Module 01-Lesson 02_Get Help from Peers and Mentors/img/screen-shot-2018-11-07-at-10.23.07-pm.png 374.8 kB
Part 01-Module 02-Lesson 01_Get Help from Peers and Mentors/img/screen-shot-2018-11-07-at-10.23.07-pm.png 374.8 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3006898966.gif 374.7 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-commit-details-section.png 373.2 kB
Part 11-Module 01-Lesson 01_Introduction/img/screen-shot-2018-01-19-at-1.14.23-pm.png 367.2 kB
Part 08-Module 01-Lesson 02_Design of Visualizations/img/bad-viz-2.png 365.0 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3016528680.gif 363.9 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-add.gif 361.2 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3022688695.gif 359.5 kB
Part 10-Module 01-Lesson 08_Working On Another Developer's Repository/img/ud456-l2-04-lighthouse-contributing-file.png 348.6 kB
Part 06-Module 01-Lesson 06_NumPy/img/screen-shot-2018-03-19-at-3.21.24-pm.png 348.1 kB
Part 06-Module 01-Lesson 07_Pandas/img/screen-shot-2018-03-19-at-3.21.24-pm.png 348.1 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/03. Admissions 2-o91iPvtqt78.mp4 347.4 kB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/img/fbeta.png 345.2 kB
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Part 12-Module 01-Lesson 16_Logistic Regression/img/3041298589.gif 343.3 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3022138739.gif 342.5 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-github-create-repo-page.png 339.7 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/media/Markdown+cells.mp4 338.3 kB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/img/screen-shot-2018-05-26-at-7.55.02-pm.png 336.5 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-project-push-commits.png 336.1 kB
Part 10-Module 01-Lesson 08_Working On Another Developer's Repository/img/ud456-l2-04-submit-new-issue.png 335.0 kB
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Part 02-Module 01-Lesson 08_Model Evaluation Metrics/img/screen-shot-2018-05-26-at-7.55.22-pm.png 334.1 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-04-git-pull.png 333.3 kB
Part 11-Module 01-Lesson 03_Linear Combination/img/screen-shot-2018-01-26-at-11.05.49-pm.png 331.7 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/02. Admissions 1-f3y_weFskL4.mp4 330.8 kB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/img/screen-shot-2018-05-26-at-7.53.22-pm.png 329.8 kB
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Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-commit-initial-commit.png 326.3 kB
Part 10-Module 01-Lesson 08_Working On Another Developer's Repository/img/ud456-l2-03-git-shortlog.png 325.9 kB
Part 06-Module 01-Lesson 02_Data Types and Operators/img/screen-shot-2018-02-10-at-8.59.39-pm.png 322.0 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-commit-editor.png 320.6 kB
Part 12-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.mp4 320.1 kB
Part 06-Module 01-Lesson 05_Scripting/img/generate-messages-output.png 318.0 kB
Part 12-Module 01-Lesson 05_Binomial Distribution/img/48665990.gif 316.7 kB
Part 20-Module 01-Lesson 02_Deep Neural Networks/img/all-ranks.png 315.9 kB
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Part 12-Module 01-Lesson 16_Logistic Regression/img/3007308918.gif 315.2 kB
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Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-merge-conflict-prep.png 311.0 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3004608562.gif 309.1 kB
Part 02-Module 01-Lesson 04_Decision Trees/img/trees.png 307.2 kB
Part 01-Module 02-Lesson 01_Get Help from Peers and Mentors/img/screen-shot-2018-11-09-at-6.28.07-pm.png 307.2 kB
Part 13-Module 01-Lesson 02_Get Help from Peers and Mentors/img/screen-shot-2018-11-09-at-6.28.07-pm.png 307.2 kB
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Part 02-Module 01-Lesson 06_Support Vector Machines/img/screen-shot-2018-01-06-at-10.44.48-pm.png 292.3 kB
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Part 02-Module 01-Lesson 06_Support Vector Machines/img/margin-geometry-images.005.jpeg 288.1 kB
Part 14-Module 01-Lesson 01_The Data Science Process/img/screen-shot-2018-02-24-at-2.13.15-pm.png 287.6 kB
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Part 12-Module 01-Lesson 05_Binomial Distribution/img/48736116.gif 273.8 kB
Part 10-Module 01-Lesson 03_Review a Repo's History/img/ud123-l3-git-log-p-lines-removed-annotated.png 272.3 kB
Part 20-Module 01-Lesson 01_Neural Networks/img/and-quiz.png 272.2 kB
Part 02-Module 01-Lesson 03_Perceptron Algorithm/img/and-quiz.png 272.2 kB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/img/and-quiz.png 272.2 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-log-decorate.png 271.7 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3007188710.gif 268.6 kB
Part 02-Module 01-Lesson 03_Perceptron Algorithm/08. DL 10 S Perceptron Algorithm-fATmrG2hQzI.mp4 266.2 kB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.mp4 266.2 kB
Part 20-Module 01-Lesson 01_Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.mp4 266.2 kB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/img/02-guide-how-transfer-learning-v3-06.png 265.3 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3023678781.gif 264.5 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3016088789.gif 263.8 kB
Part 10-Module 01-Lesson 08_Working On Another Developer's Repository/img/ud456-l2-03-git-log-author.png 261.5 kB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/img/02-guide-how-transfer-learning-v3-04.png 261.3 kB
Part 02-Module 01-Lesson 06_Support Vector Machines/img/margin-geometry-images.003.jpeg 259.7 kB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/img/02-guide-how-transfer-learning-v3-01.png 257.3 kB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/img/precision-quiz.png 256.8 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-git-remote-add-terminal.png 255.2 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-log-graph-all.png 254.4 kB
Part 10-Module 01-Lesson 08_Working On Another Developer's Repository/img/ud456-l2-03-git-shortlog-flags.png 254.4 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3009678880.gif 254.3 kB
Part 17-Module 03-Lesson 02_Matrix Factorization for Recommendations/img/screen-shot-2018-09-14-at-10.16.10-am.png 253.6 kB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/img/02-guide-how-transfer-learning-v3-10.png 247.6 kB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/img/02-guide-how-transfer-learning-v3-08.png 247.4 kB
Part 17-Module 03-Lesson 02_Matrix Factorization for Recommendations/img/screen-shot-2018-09-13-at-6.32.03-pm.png 246.0 kB
Part 12-Module 01-Lesson 16_Logistic Regression/img/3050008540.gif 245.8 kB
Part 01-Module 02-Lesson 02_Get Help with Your Account/img/screen-shot-2018-11-09-at-7.49.34-pm.png 244.7 kB
Part 13-Module 01-Lesson 03_Get Help with Your Account/img/screen-shot-2018-11-09-at-7.49.34-pm.png 244.7 kB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/img/screen-shot-2018-05-26-at-7.24.13-pm.png 244.0 kB
Part 17-Module 03-Lesson 02_Matrix Factorization for Recommendations/img/screen-shot-2018-09-14-at-10.11.13-am.png 242.6 kB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/img/02-guide-how-transfer-learning-v3-07.png 238.9 kB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/img/02-guide-how-transfer-learning-v3-05.png 238.1 kB
assets/js/katex.min.js 236.8 kB
Part 16-Module 03-Lesson 01_Strengthen Your Online Presence Using LinkedIn/img/redacted-linkedinresults.png 236.3 kB
Part 07-Module 01-Lesson 04_SQL Subqueries Temporary Tables/img/screen-shot-2017-11-16-at-3.54.06-pm.png 235.3 kB
Part 07-Module 01-Lesson 02_SQL Joins/img/screen-shot-2017-11-16-at-3.54.06-pm.png 235.3 kB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/img/02-guide-how-transfer-learning-v3-03.png 234.4 kB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/img/recall-quiz.png 233.7 kB
Part 13-Module 01-Lesson 02_Get Help from Peers and Mentors/img/image8.png 233.5 kB
Part 01-Module 02-Lesson 01_Get Help from Peers and Mentors/img/image8.png 233.5 kB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/img/02-guide-how-transfer-learning-v3-09.png 233.5 kB
Part 12-Module 01-Lesson 15_Multiple Linear Regression/img/screen-shot-2017-12-07-at-3.45.19-pm.png 232.6 kB
Part 02-Module 01-Lesson 06_Support Vector Machines/img/margin-geometry-images.001.jpeg 231.0 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-status-with-untracked.png 228.3 kB
Part 01-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree program/img/screen-shot-2018-08-13-at-6.39.12-pm.png 228.2 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-status-after-git-add.png 227.6 kB
Part 13-Module 01-Lesson 02_Get Help from Peers and Mentors/img/screen-shot-2018-11-07-at-9.55.40-pm.png 227.5 kB
Part 01-Module 02-Lesson 01_Get Help from Peers and Mentors/img/screen-shot-2018-11-07-at-9.55.40-pm.png 227.5 kB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/img/full-padding-no-strides-transposed.gif 227.1 kB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/img/screen-shot-2018-08-07-at-4.35.30-pm.png 225.6 kB
Part 06-Module 01-Lesson 02_Data Types and Operators/img/screen-shot-2018-01-30-at-5.14.39-pm.png 225.6 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/09. Aggregation 3-tPSj6_m-0_M.mp4 225.6 kB
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/img/02-guide-how-transfer-learning-v3-02.png 224.5 kB
Part 11-Module 01-Lesson 01_Introduction/img/screen-shot-2018-01-19-at-2.24.21-pm.png 224.0 kB
Part 12-Module 01-Lesson 07_Bayes Rule/27. Robot Sensing 7-clFL503NPyY.mp4 223.5 kB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/img/screen-shot-2018-08-11-at-12.52.21-pm.png 222.5 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/media/notebook+interface.mp4 220.6 kB
Part 02-Module 01-Lesson 06_Support Vector Machines/img/margin-geometry-images.002.jpeg 220.6 kB
Part 02-Module 01-Lesson 03_Perceptron Algorithm/img/xor.png 220.1 kB
Part 20-Module 01-Lesson 01_Neural Networks/img/xor.png 220.1 kB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/img/xor.png 220.1 kB
Part 14-Module 01-Lesson 01_The Data Science Process/img/screen-shot-2018-02-24-at-2.18.30-pm.png 216.4 kB
Part 03-Module 01-Lesson 04_Keras/img/meme.png 214.1 kB
Part 02-Module 01-Lesson 05_Naive Bayes/img/meme.png 214.1 kB
Part 02-Module 01-Lesson 04_Decision Trees/img/meme.png 214.1 kB
Part 20-Module 01-Lesson 01_Neural Networks/img/meme.png 214.1 kB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/img/meme.png 214.1 kB
Part 02-Module 01-Lesson 03_Perceptron Algorithm/img/meme.png 214.1 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-status-modified-files.png 213.5 kB
Part 08-Module 01-Lesson 01_Data Visualization in Data Analysis/img/mike-josh-bios-portraits.png 213.3 kB
Part 10-Module 01-Lesson 03_Review a Repo's History/img/ud123-l3-git-log-stat.gif 211.7 kB
Part 10-Module 01-Lesson 02_Create A Git Repo/img/ud123-l2-.git-directory.png 210.7 kB
Part 11-Module 01-Lesson 02_Vectors/img/screen-shot-2018-01-24-at-3.13.49-pm.png 209.5 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/media/conda_install.mp4 206.6 kB
Part 15-Module 01-Lesson 04_Introduction to Object-Oriented Programming/img/screen-shot-2018-07-19-at-4.05.25-pm.png 206.1 kB
Part 16-Module 03-Lesson 01_Strengthen Your Online Presence Using LinkedIn/img/screen-shot-2018-02-23-at-5.11.40-pm.png 205.5 kB
Part 02-Module 01-Lesson 02_Linear Regression/img/batch-stochastic.png 201.6 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-merge-conflict.png 198.4 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-ignore-word-doc.png 197.4 kB
Part 02-Module 01-Lesson 04_Decision Trees/img/table.png 196.7 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-status-all-files.png 196.5 kB
Part 08-Module 01-Lesson 02_Design of Visualizations/img/pasted-image-0.png 196.4 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-gitignore.png 196.0 kB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/img/confusion.png 193.4 kB
Part 02-Module 01-Lesson 07_Ensemble Methods/img/screen-shot-2018-01-03-at-2.23.38-pm.png 192.4 kB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/img/medical.png 191.0 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-git-remote-from-clone.png 190.7 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-project-on-github.png 190.0 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-commit-finished.png 189.1 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-checkout-b-footer-master.png 188.3 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-project-on-github-focus.png 188.2 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-tag-delete.png 184.7 kB
Part 12-Module 01-Lesson 01_Descriptive Statistics - Part I/img/mat-headshot.png 184.3 kB
Part 03-Module 01-Lesson 02_Implementing Gradient Descent/img/mat-headshot.png 184.3 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-diff.png 183.8 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-merge-sidebar.png 181.2 kB
Part 10-Module 01-Lesson 03_Review a Repo's History/img/ud123-l3-git-status-output.png 178.4 kB
Part 02-Module 01-Lesson 02_Linear Regression/img/quiz.jpg 178.4 kB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/img/screen-shot-2018-08-07-at-6.02.41-pm.png 177.3 kB
Part 04-Module 01-Lesson 05_Random Projection and ICA/img/eeg-ica.png 175.0 kB
Part 12-Module 01-Lesson 12_Hypothesis Testing/img/screen-shot-2018-01-24-at-12.03.45-am.png 174.9 kB
Part 01-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree program/img/screen-shot-2018-08-13-at-6.26.18-pm.png 173.3 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/media/command+palette.mp4 173.2 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-status.png 171.6 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-changes-add-color.png 168.1 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/img/magic-timeit.png 161.1 kB
Part 01-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree program/img/screen-shot-2018-05-25-at-11.27.36-am.png 160.4 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/img/server-shutdown.png 159.2 kB
Part 10-Module 01-Lesson 06_Undoing Changes/img/ud123-l6-git-revert-prep.png 158.8 kB
Part 10-Module 01-Lesson 08_Working On Another Developer's Repository/img/ud456-l2-02-git-fork-error.png 158.7 kB
Part 08-Module 01-Lesson 02_Design of Visualizations/img/challenger2.gif 158.3 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-checkout-sidebar.png 157.9 kB
Part 10-Module 01-Lesson 09_Staying In Sync With A Remote Repository/img/ud456-l3-03-rename-repos.png 156.9 kB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/img/screen-shot-2018-08-11-at-12.52.03-pm.png 156.3 kB
Part 06-Module 01-Lesson 02_Data Types and Operators/img/screen-shot-2018-05-11-at-11.03.34-am.png 154.6 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-branch-sidebar.png 153.0 kB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/img/email.png 152.1 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-04-commit-count-local.png 151.1 kB
Part 10-Module 01-Lesson 02_Create A Git Repo/img/ud123-l2-git-clone.gif 150.9 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-git-remote-shortname.png 150.6 kB
Part 03-Module 01-Lesson 06_Image Classifier Project/img/workspaces-submit.png 149.7 kB
Part 03-Module 01-Lesson 06_Image Classifier Project/img/workspaces-gpu.png 149.0 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-my-travel-plans-project.png 148.8 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-branch.png 147.6 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-log-branches.png 147.3 kB
Part 10-Module 01-Lesson 09_Staying In Sync With A Remote Repository/img/ud456-l3-03-git-log-of-upstream-changes.png 147.2 kB
Part 03-Module 01-Lesson 06_Image Classifier Project/img/workspaces-notebook.png 146.3 kB
Part 17-Module 04-Lesson 01_Recommendation Engines/img/screen-shot-2018-09-17-at-3.40.30-pm.png 145.0 kB
Part 16-Module 02-Lesson 01_Project Disaster Response Pipeline/img/screen-shot-2018-02-21-at-8.05.18-pm.png 144.8 kB
Part 02-Module 01-Lesson 04_Decision Trees/img/recommending-apps.png 143.9 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-git-remote-no-remote.png 143.7 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-tag.png 143.0 kB
Part 10-Module 01-Lesson 09_Staying In Sync With A Remote Repository/img/ud456-l3-03-add-upstream-remote.png 141.2 kB
assets/css/bootstrap.min.css 140.9 kB
Part 02-Module 01-Lesson 02_Linear Regression/img/minibatch.png 140.0 kB
Part 02-Module 01-Lesson 05_Naive Bayes/img/spamham.png 138.3 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-branch-asterisk.png 138.1 kB
Part 10-Module 01-Lesson 07_Working With Remotes/img/ud456-l1-project-commits.png 135.0 kB
Part 15-Module 01-Lesson 04_Introduction to Object-Oriented Programming/img/screen-shot-2018-07-19-at-4.06.55-pm.png 133.1 kB
assets/js/plyr.polyfilled.min.js 129.2 kB
Part 11-Module 01-Lesson 01_Introduction/img/screen-shot-2018-01-19-at-1.58.00-pm.png 129.1 kB
Part 10-Module 01-Lesson 06_Undoing Changes/img/ud123-l6-git-revert-mixed.png 128.9 kB
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/img/ud123-l5-git-log-pre-tag.png 127.7 kB
Part 08-Module 01-Lesson 02_Design of Visualizations/img/natgeo-scatter.jpg 126.7 kB
Part 12-Module 01-Lesson 07_Bayes Rule/img/screen-shot-2017-08-02-at-11.49.10-am.png 123.2 kB
Part 03-Module 01-Lesson 02_Implementing Gradient Descent/img/admissions-data.png 121.2 kB
Part 11-Module 01-Lesson 04_Linear Transformation and Matrices/img/screen-shot-2018-02-14-at-6.07.26-pm.png 120.3 kB
Part 07-Module 01-Lesson 02_SQL Joins/img/screen-shot-2017-08-10-at-8.23.48-pm.png 117.9 kB
Part 11-Module 01-Lesson 01_Introduction/img/screen-shot-2018-01-19-at-1.57.42-pm.png 117.0 kB
Part 10-Module 01-Lesson 02_Create A Git Repo/img/ud123-l2-base-directory-git-repo.png 116.3 kB
Part 11-Module 01-Lesson 02_Vectors/img/screen-shot-2018-01-24-at-2.27.07-pm.png 115.9 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-git-commit-terminal-hangs.png 113.7 kB
Part 02-Module 01-Lesson 04_Decision Trees/img/screen-shot-2018-01-06-at-9.41.01-pm.png 113.4 kB
Part 13-Module 01-Lesson 03_Get Help with Your Account/img/screen-shot-2018-11-09-at-7.38.47-pm.png 113.2 kB
Part 01-Module 02-Lesson 02_Get Help with Your Account/img/screen-shot-2018-11-09-at-7.38.47-pm.png 113.2 kB
Part 10-Module 01-Lesson 04_Add Commits To A Repo/img/ud123-l4-new-git-project.png 113.1 kB
Part 10-Module 01-Lesson 03_Review a Repo's History/img/ud123-l3-git-log-p.png 112.7 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/img/conda-tab.png 112.6 kB
Part 02-Module 01-Lesson 09_Training and Tuning/img/learning-curves.png 111.6 kB
Part 12-Module 01-Lesson 07_Bayes Rule/img/screen-shot-2017-08-02-at-11.40.37-am.png 110.8 kB
Part 10-Module 01-Lesson 02_Create A Git Repo/img/ud123-l2-new-git-project.png 109.1 kB
Part 20-Module 01-Lesson 02_Deep Neural Networks/img/nn.png 108.5 kB
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/img/accuracy-quiz.png 108.4 kB
Part 08-Module 01-Lesson 02_Design of Visualizations/img/apple.jpg 107.9 kB
Part 07-Module 01-Lesson 02_SQL Joins/img/screen-shot-2017-08-14-at-4.10.54-pm.png 107.8 kB
Part 07-Module 01-Lesson 02_SQL Joins/img/screen-shot-2017-08-14-at-4.04.44-pm.png 106.0 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/img/notebook-server.png 105.8 kB
Part 11-Module 01-Lesson 04_Linear Transformation and Matrices/img/screen-shot-2018-02-14-at-3.59.39-pm.png 105.4 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/img/new-notebook.png 104.2 kB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/img/screen-shot-2018-08-11-at-12.54.48-pm.png 101.0 kB
Part 11-Module 01-Lesson 01_Introduction/img/screen-shot-2018-04-02-at-4.25.41-pm.png 99.9 kB
Part 04-Module 01-Lesson 03_Gaussian Mixture Models and Cluster Validation/img/external-indices-quiz.png 98.8 kB
Part 12-Module 01-Lesson 06_Conditional Probability/img/48271967.gif 98.4 kB
Part 13-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree Program/img/screen-shot-2018-08-27-at-3.51.23-pm.png 98.3 kB
Part 10-Module 01-Lesson 06_Undoing Changes/img/ud123-l6-git-revert-soft.png 98.1 kB
Part 02-Module 01-Lesson 09_Training and Tuning/img/complexity.png 97.9 kB
Part 06-Module 01-Lesson 02_Data Types and Operators/img/screen-shot-2018-01-30-at-4.39.42-pm.png 97.8 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/img/notebook-json.png 97.6 kB
Part 10-Module 01-Lesson 06_Undoing Changes/img/ud123-l6-git-revert-hard.png 97.4 kB
Part 16-Module 03-Lesson 01_Strengthen Your Online Presence Using LinkedIn/media/unnamed-project-desc-0.gif 96.8 kB
Part 20-Module 01-Lesson 01_Neural Networks/img/xor-quiz.png 96.4 kB
Part 02-Module 01-Lesson 03_Perceptron Algorithm/img/xor-quiz.png 96.4 kB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/img/xor-quiz.png 96.4 kB
Part 03-Module 01-Lesson 06_Image Classifier Project/img/workspaces-menu.png 96.2 kB
Part 20-Module 01-Lesson 02_Deep Neural Networks/img/summary.png 96.0 kB
Part 03-Module 01-Lesson 04_Keras/img/summary.png 96.0 kB
Part 02-Module 01-Lesson 03_Perceptron Algorithm/img/perceptronquiz.png 95.9 kB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/img/perceptronquiz.png 95.9 kB
Part 20-Module 01-Lesson 01_Neural Networks/img/perceptronquiz.png 95.9 kB
Part 10-Module 01-Lesson 01_What is Version Control/img/ud123-l1-terminal-config-windows.png 95.5 kB
Part 11-Module 01-Lesson 02_Vectors/img/screen-shot-2018-01-23-at-11.30.13-am.png 95.0 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/img/48728202.gif 94.4 kB
Part 03-Module 01-Lesson 02_Implementing Gradient Descent/img/example-data.png 94.3 kB
Part 02-Module 01-Lesson 04_Decision Trees/img/student-data.png 94.1 kB
Part 12-Module 01-Lesson 09_Normal Distribution Theory/img/48684686.gif 93.8 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/img/48698526.gif 93.2 kB
Part 12-Module 01-Lesson 06_Conditional Probability/img/48734324.gif 93.0 kB
Part 01-Module 03-Lesson 01_Setting Up Your Computer/img/magic-matplotlib.png 92.9 kB
Part 11-Module 01-Lesson 01_Introduction/img/screen-shot-2018-01-19-at-2.28.03-pm.png 92.9 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/img/48721292.gif 92.7 kB
Part 10-Module 01-Lesson 09_Staying In Sync With A Remote Repository/img/ud456-l3-03-git-remotes-origin.png 91.4 kB
Part 12-Module 01-Lesson 03_Admissions Case Study/img/48698525.gif 91.3 kB
Part 17-Module 02-Lesson 04_Portfolio Exercise Starbucks/media/New-Starbucks-Logo-1200x969.jpg 91.2 kB
Part 07-Module 01-Lesson 02_SQL Joins/img/screen-shot-2017-08-14-at-3.41.58-pm.png 90.8 kB
Part 12-Module 01-Lesson 07_Bayes Rule/img/48240997.gif 90.7 kB
Part 10-Module 01-Lesson 09_Staying In Sync With A Remote Repository/img/ud456-l3-03-fetch-upstream-changes.png 90.2 kB
Part 03-Module 01-Lesson 03_Training Neural Networks/img/regularization-quiz.png 90.0 kB
Part 20-Module 01-Lesson 02_Deep Neural Networks/img/regularization-quiz.png 90.0 kB
Part 12-Module 01-Lesson 07_Bayes Rule/img/48310768.gif 89.8 kB
Part 12-Module 01-Lesson 15_Multiple Linear Regression/img/resid2.jpg 89.2 kB
Part 12-Module 01-Lesson 07_Bayes Rule/img/48743074.gif 89.2 kB
Part 16-Module 02-Lesson 01_Project Disaster Response Pipeline/img/disaster-response-project2.png 89.0 kB
Part 12-Module 01-Lesson 06_Conditional Probability/img/48271966.gif 88.8 kB
Part 12-Module 01-Lesson 07_Bayes Rule/img/48480561.gif 88.0 kB
Part 03-Module 01-Lesson 06_Image Classifier Project/img/workspaces-new.png 87.3 kB
assets/js/jquery-3.3.1.min.js 86.9 kB
Part 12-Module 01-Lesson 06_Conditional Probability/img/48716290.gif 86.8 kB
Part 07-Module 01-Lesson 01_Basic SQL/43. Video AND and BETWEEN.html 11.4 kB
Part 14-Module 01-Lesson 01_The Data Science Process/05. Screencast Using Workspaces.html 11.3 kB
Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines/28. Quiz Types of Ratings Goals of Recommendation Systems.html 11.3 kB
Part 12-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities.html 11.3 kB
Part 12-Module 01-Lesson 12_Hypothesis Testing/04. Quiz Setting Up Hypotheses.html 11.3 kB
Part 12-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix.html 11.3 kB
Part 17-Module 02-Lesson 01_Concepts in Experiment Design/09. Checking Bias.html 11.3 kB
Part 14-Module 01-Lesson 01_The Data Science Process/34. Notebook + Quiz Imputation Methods Resources.html 11.3 kB
Part 14-Module 01-Lesson 01_The Data Science Process/12. Notebook + Quiz How To Break Into the Field.html 11.3 kB
Part 12-Module 01-Lesson 12_Hypothesis Testing/08. Quiz Types of Errors - Part I.html 11.3 kB
Part 14-Module 01-Lesson 01_The Data Science Process/42. Notebook + Quiz Putting It All Together .html 11.3 kB
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Part 10-Module 01-Lesson 01_What is Version Control/04. MacLinux Setup.html 11.3 kB
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Part 17-Module 04-Lesson 01_Recommendation Engines/Project Rubric - Recommendations with IBM.html 11.2 kB
Part 12-Module 01-Lesson 07_Bayes Rule/13. Normalizing Probability.html 11.2 kB
Part 07-Module 01-Lesson 01_Basic SQL/30. Video Arithmetic Operators.html 11.2 kB
Part 16-Module 01-Lesson 04_Machine Learning Pipelines/20. Using Grid Search with Pipelines.html 11.2 kB
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Part 03-Module 01-Lesson 01_Introduction to Neural Networks/32. Multiclass Classification-uNTtvxwfox0.en.vtt 2.1 kB
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Part 02-Module 01-Lesson 01_Machine Learning Bird's Eye View/02. History - Statisticians Perspective-zNNouqLGF9E.en.vtt 2.1 kB
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Part 12-Module 01-Lesson 12_Hypothesis Testing/03. Setting Up Hypotheses - Part I-NpZxJg4S6X4.zh-CN.vtt 2.1 kB
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Part 16-Module 03-Lesson 01_Strengthen Your Online Presence Using LinkedIn/04. Elevator Pitch-0QtgTG49E9I.en.vtt 2.1 kB
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Part 07-Module 01-Lesson 02_SQL Joins/03. Your First JOIN-HkX9fkNRbU8.en.vtt 2.1 kB
Part 07-Module 01-Lesson 05_SQL Data Cleaning/05. Cleaning With More Advanced String Functions-E6cK8RbYGEc.zh-CN.vtt 2.1 kB
Part 06-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.en.vtt 2.1 kB
Part 12-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.en.vtt 2.1 kB
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Part 06-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.en.vtt 2.1 kB
Part 07-Module 01-Lesson 05_SQL Data Cleaning/14. COALESCE-86vgu-ECBCQ.ar.vtt 2.1 kB
Part 12-Module 01-Lesson 09_Normal Distribution Theory/15. Summary-VP-PMcgqhc8.ar.vtt 2.1 kB
Part 07-Module 01-Lesson 01_Basic SQL/43. AND BETWEEN Operators-nBuDPneWcKY.zh-CN.vtt 2.1 kB
Part 20-Module 01-Lesson 01_Neural Networks/17. One-Hot Encoding-AePvjhyvsBo.pt-BR.vtt 2.1 kB
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/17. One-Hot Encoding-AePvjhyvsBo.pt-BR.vtt 2.1 kB
Part 08-Module 01-Lesson 02_Design of Visualizations/08. What Experts Say About Visual Encodings-98aog0eVcC4.zh-CN.vtt 2.1 kB
Part 17-Module 02-Lesson 02_Statistical Considerations in Testing/img/c03-practicalsignificance-02.png 2.1 kB
Part 10-Module 01-Lesson 07_Working With Remotes/03. L1 - New Repo Git Commands On GitHub-myuGLZLYpYY.pt-BR.vtt 2.1 kB
Part 08-Module 01-Lesson 01_Data Visualization in Data Analysis/03. Further Motivation-sjGxUKrbKoI.ar.vtt 2.1 kB
Part 04-Module 01-Lesson 03_Gaussian Mixture Models and Cluster Validation/05. MLND - Unsupervised Learning - L3 05 Gaussian Distribution In 2D MAIN V1 V2-Ne-qRjO38qQ.pt-BR.vtt 2.1 kB
Part 09-Module 01-Lesson 01_Shell Workshop/06. Ud206 007 Shell P4 - Current Working Directory-X7dsy3oMHp0.pt-BR.vtt 2.1 kB
Part 07-Module 01-Lesson 02_SQL Joins/14. JOINs-CxuHtd1Daqk.zh-CN.vtt 2.1 kB
Part 08-Module 01-Lesson 04_Bivariate Exploration of Data/06. L4 061 Violin Plots 2 V3-0hr61L-LZyM.pt-BR.vtt 2.0 kB
Part 12-Module 01-Lesson 01_Descriptive Statistics - Part I/05. Data Types-gT6EYlsLZkE.pt-BR.vtt 2.0 kB
Part 12-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.it.vtt 2.0 kB
Part 02-Module 01-Lesson 01_Machine Learning Bird's Eye View/04. Types Of Machine Learning - Supervised-Jn3xugBvs2U.pt-BR.vtt 2.0 kB
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Part 12-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/12. Notation Parameters vs. Statistics-webref_dLrA.ar.vtt 2.0 kB
Part 16-Module 03-Lesson 01_Strengthen Your Online Presence Using LinkedIn/04. Elevator Pitch-0QtgTG49E9I.es-MX.vtt 2.0 kB
Part 16-Module 03-Lesson 01_Strengthen Your Online Presence Using LinkedIn/04. Elevator Pitch-0QtgTG49E9I.zh-CN.vtt 2.0 kB
Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/09. MLND - Unsupervised Learning - L2 07 HC Examples Applications MAIN V1 V2-HTahFoQwk2g.pt-BR.vtt 2.0 kB
Part 12-Module 01-Lesson 12_Hypothesis Testing/24. Conclusions In Hypothesis Testing-I0Mo7hcxahY.pt-BR.vtt 2.0 kB
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Part 12-Module 01-Lesson 12_Hypothesis Testing/07. Types Of Errors - Part I-aw6GMxIvENc.pt-BR.vtt 2.0 kB
Part 12-Module 01-Lesson 13_Case Study AB tests/04. Business Example-Wzz7omSDfEk.en.vtt 2.0 kB
Part 12-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/23. Bootstrapping the Central Limit Theorem-GJGUwNr_82s.zh-CN.vtt 2.0 kB
Part 12-Module 01-Lesson 01_Descriptive Statistics - Part I/15. The Median-WlT3eeW0rb0.zh-CN.vtt 2.0 kB
Part 07-Module 01-Lesson 03_SQL Aggregations/05. COUNT NULLs-ngxgqfFFFLQ.pt-BR.vtt 2.0 kB
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Part 04-Module 01-Lesson 03_Gaussian Mixture Models and Cluster Validation/08. MLND - Unsupervised Learning - L3 08 Overview Of The Expectation Maximization Algorithm MAIN V1 V1-XdQfFnnj5Xo.pt-BR.vtt 2.0 kB
Part 07-Module 01-Lesson 03_SQL Aggregations/03. Data Types and NULLs-RgTcYwKqtYI.zh-CN.vtt 2.0 kB
Part 01-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree program/07. Meet The Instructors-ndyjFUF2e9Q.pt-BR.vtt 2.0 kB
Part 12-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.ja.vtt 2.0 kB
Part 12-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.es-ES.vtt 2.0 kB
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Part 12-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.ar.vtt 2.0 kB
Part 12-Module 01-Lesson 12_Hypothesis Testing/24. Conclusions In Hypothesis Testing-I0Mo7hcxahY.en.vtt 2.0 kB
Part 10-Module 01-Lesson 07_Working With Remotes/02. L1 - Remote Repos Intro-AnSlYftJnwA.zh-CN.vtt 2.0 kB
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Part 12-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.pt-BR.vtt 2.0 kB
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Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/09. Writing READMEs with Walter-DQEfT2Zq5_o.en.vtt 1.4 kB
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Part 12-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/07. Example of Sampling Distributions - Part II-PKf3Nu6zAxM.ar.vtt 1.4 kB
Part 02-Module 01-Lesson 10_Finding Donors Project/01. ML Charity Project-aVodYHcOB8U.en.vtt 1.4 kB
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Part 14-Module 01-Lesson 01_The Data Science Process/38. Working With Categorical Variables-IoQOiuxsIZg.en.vtt 1.3 kB
Part 07-Module 01-Lesson 01_Basic SQL/09. Types Of Statements-vLvJbIz94C4.zh-CN.vtt 1.3 kB
Part 03-Module 01-Lesson 06_Image Classifier Project/01. PROJECT INTRO MAIN V2---9IFCNBM6Y.en.vtt 1.3 kB
Part 01-Module 01-Lesson 01_Welcome to the Data Scientist Nanodegree program/02. INTRODUÇÃO AO PROJETO PRINCIPAL V2---9IFCNBM6Y.en.vtt 1.3 kB
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Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile-ncFtwW5urHk.zh-CN.vtt 1.3 kB
Part 04-Module 01-Lesson 05_Random Projection and ICA/03. L6 2 Random Projection Impl MAINv1 V1 V1-5DhvurLgRII.pt-BR.vtt 1.3 kB
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Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/09. Writing READMEs with Walter-DQEfT2Zq5_o.pt-BR.vtt 1.3 kB
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Part 07-Module 01-Lesson 06_[Advanced] SQL Window Functions/20. Percentiles-Qro8uvysnys.en.vtt 1.2 kB
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Part 04-Module 01-Lesson 01_Clustering/01. Introduction-k7YOVTkFRJM.en.vtt 1.2 kB
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Part 12-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.th.vtt 1.2 kB
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Part 07-Module 01-Lesson 03_SQL Aggregations/06. SUM-0zUP14PeiXk.pt-BR.vtt 1.2 kB
Part 12-Module 01-Lesson 06_Conditional Probability/14. Two Coins 4-9R44IyZ-aQI.pt-BR.vtt 1.2 kB
Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/02. MLND - Unsupervised Learning - L2 02 V1-Ed6RKuBzKWA.en.vtt 1.2 kB
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Part 04-Module 01-Lesson 04_PCA/21. Outro-CuIqzL8HjI8.en.vtt 817 Bytes
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Part 12-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.pt-BR.vtt 802 Bytes
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Part 12-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.it.vtt 797 Bytes
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Part 12-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.pt-BR.vtt 780 Bytes
Part 07-Module 01-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/05. JOINs with Comparison Operators Motivation-ClzbfQyhNro.zh-CN.vtt 780 Bytes
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Part 12-Module 01-Lesson 07_Bayes Rule/19. Disease Test 6-OdVAt79eQak.en.vtt 772 Bytes
Part 02-Module 01-Lesson 04_Decision Trees/13. MLND SL DT 10 Q Information Gain MAIN V1-tVLOLPEtLFw.en.vtt 771 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.pt-BR.vtt 769 Bytes
Part 12-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.pt-BR.vtt 769 Bytes
Part 04-Module 01-Lesson 02_Hierarchical and Density Based Clustering/12. MLND - Unsupervised Learning - L2 09 DBSCAN Implementation MAIN V1 V1-qEMUzQFylg8.zh-CN.vtt 769 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-GlmS_jox08s.th.vtt 768 Bytes
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Part 12-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.it.vtt 767 Bytes
Part 14-Module 01-Lesson 01_The Data Science Process/01. Introduction-VpxATYHhKM8.pt-BR.vtt 767 Bytes
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Part 12-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-HjpgML5zsUE.zh-CN.vtt 763 Bytes
Part 06-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.en.vtt 763 Bytes
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Part 07-Module 01-Lesson 02_SQL Joins/02. Why Not Store Everything in One Table-rvY4A6FpS40.zh-CN.vtt 761 Bytes
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Part 12-Module 01-Lesson 05_Binomial Distribution/01. Binomial-3koDdc9r73E.zh-CN.vtt 759 Bytes
Part 08-Module 01-Lesson 07_Visualization Case Study/01. L7 011 Intro V1-Virihwp36do.pt-BR.vtt 759 Bytes
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Part 12-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.en.vtt 756 Bytes
Part 12-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.en.vtt 754 Bytes
Part 07-Module 01-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.pt-BR.vtt 753 Bytes
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Part 12-Module 01-Lesson 05_Binomial Distribution/10. Binomial 1-07vOaYwecII.zh-CN.vtt 751 Bytes
Part 12-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/01. Introduction-SvdlBB-ZjcQ.zh-CN.vtt 750 Bytes
Part 12-Module 01-Lesson 14_Regression/21. Recap-DzMi27LI5l4.zh-CN.vtt 750 Bytes
Part 12-Module 01-Lesson 03_Admissions Case Study/07. Aggregation-55eZrE82TqA.hr.vtt 748 Bytes
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Part 12-Module 01-Lesson 04_Probability/11. Two Flips 4-bNoS6LQEFrI.es-ES.vtt 748 Bytes
Part 12-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.pt-BR.vtt 747 Bytes
Part 12-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.ar.vtt 747 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.es-ES.vtt 746 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.es-ES.vtt 746 Bytes
Part 06-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.pt-BR.vtt 746 Bytes
Part 12-Module 01-Lesson 05_Binomial Distribution/08. Formula-DTdS-LlMTQ0.zh-CN.vtt 745 Bytes
Part 12-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.pt-BR.vtt 745 Bytes
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/07. Accuracy 2-ueYCLfd_aNQ.en-US.vtt 716 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.en.vtt 715 Bytes
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Part 12-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.en.vtt 714 Bytes
Part 12-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.zh-CN.vtt 713 Bytes
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Part 12-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.ja.vtt 710 Bytes
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Part 12-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-qDGSvvabN18.zh-CN.vtt 708 Bytes
Part 12-Module 01-Lesson 03_Admissions Case Study/11. Dangers Of Statistics-UYZXqP562qg.zh-CN.vtt 707 Bytes
Part 12-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.ar.vtt 706 Bytes
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-ZwMY5rAAd7Q.pt-BR.vtt 705 Bytes
Part 12-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.pt-BR.vtt 705 Bytes
Part 12-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.en.vtt 704 Bytes
Part 12-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/08. Example of Sampling Distributions - Part 3-E_4lvTWkSNI.zh-CN.vtt 704 Bytes
Part 12-Module 01-Lesson 06_Conditional Probability/12. Two Coins 2-tI0J14yQr1s.pt-BR.vtt 702 Bytes
Part 12-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.it.vtt 702 Bytes
Part 07-Module 01-Lesson 06_[Advanced] SQL Window Functions/19. Introduction to Percentiles-t7SX2ZEdxKA.zh-CN.vtt 701 Bytes
Part 02-Module 01-Lesson 06_Support Vector Machines/02. SVM 01 Which Line Is Better V1-NCml_NCvd1I.en.vtt 701 Bytes
Part 14-Module 01-Lesson 01_The Data Science Process/01. Introduction-VpxATYHhKM8.en.vtt 700 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/04. Normalizing 1-9SbUxcyDTaQ.th.vtt 700 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.pt-BR.vtt 699 Bytes
Part 12-Module 01-Lesson 16_Logistic Regression/21. Powell Precision and Recall-q_zfkCwRg1w.zh-CN.vtt 698 Bytes
Part 12-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.it.vtt 697 Bytes
Part 12-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.pt-BR.vtt 696 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.pt-BR.vtt 695 Bytes
Part 12-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.it.vtt 695 Bytes
Part 10-Module 01-Lesson 07_Working With Remotes/07. Lesson Wrap Up-6Koa4nAu-04.zh-CN.vtt 695 Bytes
Part 12-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.pt-BR.vtt 695 Bytes
Part 12-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.pt-BR.vtt 694 Bytes
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/01. Introducing Alexis-38ExGpdyvJI.en.vtt 694 Bytes
Part 04-Module 01-Lesson 03_Gaussian Mixture Models and Cluster Validation/13. MLND - Unsupervised Learning - L3 13 GMM Implementation MAIN V1 V2-zWrC_2Npy9E.pt-BR.vtt 694 Bytes
Part 12-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.pt-BR.vtt 692 Bytes
Part 12-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.pt-BR.vtt 692 Bytes
Part 12-Module 01-Lesson 05_Binomial Distribution/15. Binomial 6-n_OrWrZ8tKY.pt-BR.vtt 691 Bytes
Part 12-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.es-ES.vtt 671 Bytes
Part 12-Module 01-Lesson 10_Sampling distributions and the Central Limit Theorem/17. Two Useful Theorems - Central Limit Theorem-L79u8ywRmG8.zh-CN.vtt 670 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/18. Disease Test 5-nUxwwMNKIYo.ar.vtt 670 Bytes
Part 12-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.ja.vtt 669 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/25. Robot Sensing 5-PGG9agooCvw.th.vtt 667 Bytes
Part 10-Module 01-Lesson 07_Working With Remotes/04. L1 - Git Push In Theory-21TvMEtMRys.pt-BR.vtt 666 Bytes
Part 10-Module 01-Lesson 07_Working With Remotes/04. L1 - Git Push In Theory-21TvMEtMRys.en.vtt 665 Bytes
Part 12-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.es-ES.vtt 665 Bytes
Part 12-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.hr.vtt 662 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.ja.vtt 661 Bytes
Part 12-Module 01-Lesson 16_Logistic Regression/28. Equation for Recall-j2SP83afRS0.en.vtt 658 Bytes
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Part 20-Module 01-Lesson 02_Deep Neural Networks/29. Conclusion-wOiUQDgGD9E.zh-CN.vtt 655 Bytes
Part 12-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.en.vtt 655 Bytes
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Part 06-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.ar.vtt 652 Bytes
Part 10-Module 01-Lesson 06_Undoing Changes/05. Undoing Changes--_PPVk2UZMU.en.vtt 651 Bytes
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 54 Content On Different Branches-Px6EUylw8Uw.en.vtt 651 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/03. Better Formula-vMAl1m8ZtoI.ar.vtt 650 Bytes
Part 12-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.ar.vtt 650 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/05. Quadratics 2-N-wpkttwcoA.zh-CN.vtt 650 Bytes
Part 07-Module 01-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.en.vtt 650 Bytes
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Part 06-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.en.vtt 645 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-w5qcGO8krMw.zh-CN.vtt 644 Bytes
Part 12-Module 01-Lesson 14_Regression/01. Regression Introduction-PKqSS0TzXeA.zh-CN.vtt 643 Bytes
Part 07-Module 01-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION 2-so5zydnbYEg.zh-CN.vtt 643 Bytes
Part 12-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.pt-BR.vtt 642 Bytes
Part 12-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.hr.vtt 640 Bytes
Part 12-Module 01-Lesson 04_Probability/14. One Head 2-64EjAbqrtmo.ar.vtt 640 Bytes
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 54 Content On Different Branches-Px6EUylw8Uw.zh-CN.vtt 639 Bytes
Part 07-Module 01-Lesson 04_SQL Subqueries Temporary Tables/02. Introduction to Subqueries-s8ZJMj4gscY.en.vtt 639 Bytes
Part 02-Module 01-Lesson 06_Support Vector Machines/02. SVM 01 Which Line Is Better V1-NCml_NCvd1I.pt-BR.vtt 638 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.zh-CN.vtt 638 Bytes
Part 12-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.hr.vtt 637 Bytes
Part 12-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.en.vtt 635 Bytes
Part 04-Module 01-Lesson 03_Gaussian Mixture Models and Cluster Validation/13. MLND - Unsupervised Learning - L3 13 GMM Implementation MAIN V1 V2-zWrC_2Npy9E.en.vtt 635 Bytes
Part 12-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-VLLG0rYC7To.th.vtt 634 Bytes
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/16. Starring interesting repositories-ZwMY5rAAd7Q.en.vtt 634 Bytes
Part 20-Module 01-Lesson 02_Deep Neural Networks/01. Non-Linear Data-F7ZiE8PQiSc.en.vtt 633 Bytes
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/30. Non-Linear Data-F7ZiE8PQiSc.en.vtt 633 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/01. Bayes Rules-CohZnkZMOxE.zh-CN.vtt 633 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.en.vtt 633 Bytes
Part 12-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.it.vtt 618 Bytes
Part 12-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.pt-BR.vtt 618 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/05. Normalizing 2-WYA5Zbf8HC4.ja.vtt 618 Bytes
Part 02-Module 01-Lesson 08_Model Evaluation Metrics/07. Accuracy 2-ueYCLfd_aNQ.pt-BR.vtt 618 Bytes
Part 12-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.ru.vtt 617 Bytes
Part 12-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.en.vtt 617 Bytes
Part 12-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.ja.vtt 617 Bytes
Part 12-Module 01-Lesson 08_Python Probability Practice/08. Python Probability Conclusion-4JYar5GykXk.zh-CN.vtt 617 Bytes
Part 12-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.en-US.vtt 617 Bytes
Part 12-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.en.vtt 617 Bytes
Part 10-Module 01-Lesson 05_Tagging, Branching, and Merging/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 54 Content On Different Branches-Px6EUylw8Uw.pt-BR.vtt 617 Bytes
Part 12-Module 01-Lesson 06_Conditional Probability/11. Two Coins 1-QIQBb4nLsHc.zh-CN.vtt 616 Bytes
Part 12-Module 01-Lesson 03_Admissions Case Study/14. Conclusion-XiR_37bYA84.zh-CN.vtt 616 Bytes
Part 10-Module 01-Lesson 07_Working With Remotes/04. L1 - Git Push In Theory-21TvMEtMRys.zh-CN.vtt 616 Bytes
Part 07-Module 01-Lesson 07_[Advanced] SQL Advanced JOINs Performance Tuning/11. UNION Motivation-0eRr2K8lo-I.zh-CN.vtt 616 Bytes
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/01. Introducing Alexis-38ExGpdyvJI.zh-CN.vtt 615 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/10. Cancer Probabilities-CMQBKuYjPBM.ar.vtt 615 Bytes
Part 12-Module 01-Lesson 01_Descriptive Statistics - Part I/17. Measures of Center - The Mode-NE81NZgECqg.zh-CN.vtt 613 Bytes
Part 12-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.es-ES.vtt 611 Bytes
Part 12-Module 01-Lesson 16_Logistic Regression/27. Equation for Precision-CStZqZRe6Mk.en.vtt 610 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/11. Probability Given Test-omC0zbJyzUY.zh-CN.vtt 609 Bytes
Part 14-Module 02-Lesson 01_Optimize Your GitHub Profile/08. Quick Fixes #2-It6AEuSDQw0.ar.vtt 608 Bytes
Part 12-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.ja.vtt 608 Bytes
Part 12-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.es-ES.vtt 608 Bytes
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/21. Formula For Cross 1-qvr_ego_d6w.en.vtt 607 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-5zkupL6EWh8.ar.vtt 607 Bytes
Part 20-Module 01-Lesson 01_Neural Networks/21. Formula For Cross 1-qvr_ego_d6w.en.vtt 607 Bytes
Part 12-Module 01-Lesson 06_Conditional Probability/07. Medical Example 6--lC9xztr4zA.th.vtt 604 Bytes
Part 12-Module 01-Lesson 04_Probability/09. Two Flips 2-pT0FXiH_5nI.th.vtt 603 Bytes
Part 01-Module 03-Lesson 01_Setting Up Your Computer/20. L2 02 Outro REPLACEMENT-W-6Se0G_FVE.en.vtt 603 Bytes
Part 07-Module 01-Lesson 05_SQL Data Cleaning/17. Data Cleaning Conclusion-KkHqnvD9BWY.pt-BR.vtt 602 Bytes
Part 20-Module 01-Lesson 02_Deep Neural Networks/01. Non-Linear Data-F7ZiE8PQiSc.pt-BR.vtt 600 Bytes
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/30. Non-Linear Data-F7ZiE8PQiSc.pt-BR.vtt 600 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.en.vtt 599 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-Ny2vcRZ6Aws.ar.vtt 599 Bytes
Part 12-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-NRPcnpmFCg8.pt-BR.vtt 599 Bytes
Part 20-Module 01-Lesson 03_Convolutional Neural Networks/01. Introducing Alexis-38ExGpdyvJI.pt-BR.vtt 599 Bytes
Part 12-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.hr.vtt 599 Bytes
Part 12-Module 01-Lesson 13_Case Study AB tests/01. Case Study Introduction-J5uvdPxHIfs.en.vtt 598 Bytes
Part 12-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.pt-BR.vtt 598 Bytes
Part 12-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.it.vtt 598 Bytes
Part 12-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.ja.vtt 597 Bytes
Part 10-Module 01-Lesson 06_Undoing Changes/05. Undoing Changes--_PPVk2UZMU.zh-CN.vtt 597 Bytes
Part 12-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.pt-BR.vtt 597 Bytes
Part 12-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.ja.vtt 596 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.es-ES.vtt 595 Bytes
Part 12-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.ja.vtt 594 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.pt-BR.vtt 593 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/07. Quadratics 4-yimIE9fCvi8.en.vtt 591 Bytes
Part 12-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.ar.vtt 591 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/08. Maximum-MZoYGBZTh-g.ja.vtt 589 Bytes
Part 12-Module 01-Lesson 06_Conditional Probability/09. Medical Example 8-btGdX0ZpkNU.pt-BR.vtt 589 Bytes
Part 02-Module 01-Lesson 06_Support Vector Machines/02. SVM 01 Which Line Is Better V1-NCml_NCvd1I.zh-CN.vtt 588 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/06. Quadratics 3-YSMWpFM92S0.ja.vtt 587 Bytes
Part 03-Module 01-Lesson 04_Keras/06. Keras Lab-a50un22BsLI.en.vtt 586 Bytes
Part 12-Module 01-Lesson 13_Case Study AB tests/18. Conclusion-qmGjRpMVBz8.en.vtt 586 Bytes
Part 20-Module 01-Lesson 02_Deep Neural Networks/26. Keras Lab-a50un22BsLI.en.vtt 586 Bytes
Part 20-Module 01-Lesson 01_Neural Networks/15. Discrete vs Continuous-rdP-RPDFkl0.pt-BR.vtt 584 Bytes
Part 12-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.ja.vtt 584 Bytes
Part 03-Module 01-Lesson 01_Introduction to Neural Networks/15. Discrete vs Continuous-rdP-RPDFkl0.pt-BR.vtt 584 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/22. Robot Sensing 2-t22oDruXhuo.ar.vtt 584 Bytes
Part 06-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.pt-BR.vtt 583 Bytes
Part 12-Module 01-Lesson 12_Hypothesis Testing/01. Hypothesis Testing Introduction-Qi6F2rJAmrA.pt-BR.vtt 582 Bytes
Part 12-Module 01-Lesson 16_Logistic Regression/13. Filling in a Confusion Matrix-FwaYsmnlLM4.ar.vtt 582 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/14. Central Limit Theorem-36KLIHioAvA.zh-CN.vtt 582 Bytes
Part 12-Module 01-Lesson 04_Probability/07. Complementary Outcomes-YseJqD-1oUg.zh-CN.vtt 582 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/37. Bayes Rule Conclusion-vlfDGCD8w0s.pt-BR.vtt 579 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/07. Total Probability-fAaE5K9OZJc.th.vtt 579 Bytes
Part 12-Module 01-Lesson 03_Admissions Case Study/04. Admissions 3-iKTYAsZLbhc.zh-Hans.vtt 579 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/10. Minimum-MEbJxfw3NVs.zh-CN.vtt 579 Bytes
Part 12-Module 01-Lesson 04_Probability/04. Loaded Coin 1-T0EjWSjLGjQ.th.vtt 578 Bytes
Part 12-Module 01-Lesson 04_Probability/13. One Head 1-T4A5uyqesjo.zh-CN.vtt 577 Bytes
Part 12-Module 01-Lesson 16_Logistic Regression/33. Congrats-Qy8VYdqoxGA.pt-BR.vtt 576 Bytes
Part 12-Module 01-Lesson 04_Probability/13. One Head 1-lHuZpDkfwq8.es-ES.vtt 575 Bytes
Part 12-Module 01-Lesson 04_Probability/12. Two Flips 5-HB8b7sZQFGs.hr.vtt 575 Bytes
Part 12-Module 01-Lesson 16_Logistic Regression/17. How Many Schroeder Predictions-n7gp8USw0Jw.en.vtt 575 Bytes
Part 20-Module 01-Lesson 02_Deep Neural Networks/26. Keras Lab-a50un22BsLI.pt-BR.vtt 574 Bytes
Part 03-Module 01-Lesson 04_Keras/06. Keras Lab-a50un22BsLI.pt-BR.vtt 574 Bytes
Part 12-Module 01-Lesson 05_Binomial Distribution/12. Binomial 3-Jp2xJOtNQZ0.ja.vtt 572 Bytes
Part 12-Module 01-Lesson 13_Case Study AB tests/14. Analyzing Multiple Metrics-DtZghKNa7Ak.en.vtt 572 Bytes
Part 12-Module 01-Lesson 07_Bayes Rule/14. Disease Test 1-05upwXtARuo.zh-CN.vtt 572 Bytes
Part 12-Module 01-Lesson 04_Probability/17. Even Roll-M3L0a5V4Nf0.it.vtt 571 Bytes
Part 12-Module 01-Lesson 09_Normal Distribution Theory/04. Quadratics-GzRNoodJZxk.en.vtt 571 Bytes
Part 12-Module 01-Lesson 04_Probability/02. Flipping Coins-lgUDXtUyLLg.pt-BR.vtt 570 Bytes
Part 06-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.zh-CN.vtt 569 Bytes
Part 12-Module 01-Lesson 04_Probability/18. Doubles-On_Guw8wac8.en.vtt 569 Bytes