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05 Getting Started with Gradient Descent/068 Why a Learning Rate.mp4 196.4 MB
06 Gradient Descent with Tensorflow/084 How it All Works Together.mp4 150.8 MB
02 Algorithm Overview/022 Investigating Optimal K Values.mp4 135.4 MB
05 Getting Started with Gradient Descent/062 Understanding Gradient Descent.mp4 132.9 MB
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Complete 2020 Data Science & Machine Learning Bootcamp/4. Introduction to Optimisation and the Gradient Descent Algorithm/8. [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 305.5 MB
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Complete 2020 Data Science & Machine Learning Bootcamp/10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/12. Model Evaluation and the Confusion Matrix.mp4 264.1 MB
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Complete 2020 Data Science & Machine Learning Bootcamp/4. Introduction to Optimisation and the Gradient Descent Algorithm/10. Understanding the Learning Rate.mp4 248.1 MB
Complete 2020 Data Science & Machine Learning Bootcamp/3. Python Programming for Data Science and Machine Learning/10. [Python] - Module Imports.mp4 243.4 MB
Complete 2020 Data Science & Machine Learning Bootcamp/4. Introduction to Optimisation and the Gradient Descent Algorithm/9. [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 229.7 MB
Complete 2020 Data Science & Machine Learning Bootcamp/10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/10. Use the Model to Make Predictions.mp4 228.9 MB
Complete 2020 Data Science & Machine Learning Bootcamp/5. Predict House Prices with Multivariable Linear Regression/14. Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 224.8 MB
Complete 2020 Data Science & Machine Learning Bootcamp/11. Use Tensorflow to Classify Handwritten Digits/12. Different Model Architectures Experimenting with Dropout.mp4 224.1 MB
Complete 2020 Data Science & Machine Learning Bootcamp/8. Test and Evaluate a Naive Bayes Classifier Part 3/6. Visualising the Decision Boundary.mp4 215.3 MB
Complete 2020 Data Science & Machine Learning Bootcamp/8. Test and Evaluate a Naive Bayes Classifier Part 3/11. A Naive Bayes Implementation using SciKit Learn.mp4 204.6 MB
Complete 2020 Data Science & Machine Learning Bootcamp/4. Introduction to Optimisation and the Gradient Descent Algorithm/11. How to Create 3-Dimensional Charts.mp4 202.9 MB
Complete 2020 Data Science & Machine Learning Bootcamp/3. Python Programming for Data Science and Machine Learning/18. How to Make Sense of Python Documentation for Data Visualisation.mp4 179.8 MB
Complete 2020 Data Science & Machine Learning Bootcamp/3. Python Programming for Data Science and Machine Learning/19. Working with Python Objects to Analyse Data.mp4 178.2 MB
Complete 2020 Data Science & Machine Learning Bootcamp/5. Predict House Prices with Multivariable Linear Regression/11. Visualising Correlations with a Heatmap.mp4 176.8 MB
Complete 2020 Data Science & Machine Learning Bootcamp/3. Python Programming for Data Science and Machine Learning/17. [Python] - Objects - Understanding Attributes and Methods.mp4 164.4 MB
Complete 2020 Data Science & Machine Learning Bootcamp/11. Use Tensorflow to Classify Handwritten Digits/11. Name Scoping and Image Visualisation in Tensorboard.mp4 162.9 MB
Complete 2020 Data Science & Machine Learning Bootcamp/3. Python Programming for Data Science and Machine Learning/9. [Python & Pandas] - Dataframes and Series.mp4 160.7 MB
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07. Regression Analysis/3. [Hands On] - Linear Regression model using OLS.mp4 95.5 MB
12. Text Analytics and Natural Language Processing/5. [Hands On] - Classify Customer Complaints using Text Analytics.mp4 95.4 MB
12. Text Analytics and Natural Language Processing/4. Feature Hashing.mp4 78.8 MB
01. Basics of Machine Learning/4. Why Machine Learning is the Future.mp4 72.1 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/9. [Hands On] - Fisher Based LDA - Experiment.mp4 64.1 MB
01. Basics of Machine Learning/5. What is Machine Learning.mp4 57.4 MB
12. Text Analytics and Natural Language Processing/2. Text Pre-Processing.mp4 57.3 MB
04. Classification/2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.mp4 54.7 MB
12. Text Analytics and Natural Language Processing/3. Bag Of Words and N-Gram Models for Text features.mp4 52.4 MB
13. Thank You and Bonus Lecture/1. Way Forward.mp4 51.6 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/2. Pearson Correlation Coefficient.mp4 49.5 MB
12. Text Analytics and Natural Language Processing/1. What is Text Analytics or Natural Language Processing.mp4 42.7 MB
03. Data Processing/5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.mp4 40.8 MB
11. Recommendation System/5. [Hands On] - Restaurant Recommendation Experiment.mp4 37.9 MB
03. Data Processing/6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.mp4 37.2 MB
04. Classification/12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.mp4 36.8 MB
11. Recommendation System/1. What is a Recommendation System.mp4 36.7 MB
08. Clustering/2. [Hands On] - Cluster Analysis Experiment 1.mp4 32.4 MB
04. Classification/4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.mp4 30.9 MB
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【影视】 [FreeCourseSite.com] Udemy - Unsupervised Machine Learning Hidden Markov Models in Python

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10. Appendix/2. Windows-Focused Environment Setup 2018.mp4 195.4 MB
10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
4. Hidden Markov Models for Discrete Observations/11. Discrete HMM in Code.mp4 49.7 MB
6. HMMs for Continuous Observations/3. Continuous-Observation HMM in Code (part 1).mp4 49.0 MB
6. HMMs for Continuous Observations/5. Continuous HMM in Theano.mp4 47.6 MB
10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
10. Appendix/11. What order should I take your courses in (part 2).mp4 39.5 MB
5. Discrete HMMs Using Deep Learning Libraries/3. Discrete HMM in Theano.mp4 32.2 MB
10. Appendix/10. What order should I take your courses in (part 1).mp4 30.8 MB
4. Hidden Markov Models for Discrete Observations/13. Discrete HMM Updates in Code with Scaling.mp4 30.6 MB
3. Markov Models Example Problems and Applications/4. Example Application Build a 2nd-order language model and generate phrases.mp4 28.2 MB
5. Discrete HMMs Using Deep Learning Libraries/4. Improving our Gradient Descent-Based HMM.mp4 27.2 MB
10. Appendix/4. How to Code by Yourself (part 1).mp4 25.7 MB
7. HMMs for Classification/2. HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).mp4 25.6 MB
5. Discrete HMMs Using Deep Learning Libraries/2. Theano Scan Tutorial.mp4 24.9 MB
5. Discrete HMMs Using Deep Learning Libraries/5. Tensorflow Scan Tutorial.mp4 24.2 MB
5. Discrete HMMs Using Deep Learning Libraries/1. Gradient Descent Tutorial.mp4 23.9 MB
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【影视】 [Tutorialsplanet.NET] Udemy - Python for Data Science and Machine Learning Bootcamp

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25. Neural Nets and Deep Learning/31. Tensorboard.mp4 151.2 MB
25. Neural Nets and Deep Learning/24. Keras Project Solutions - Dealing with Missing Data.mp4 150.6 MB
25. Neural Nets and Deep Learning/16. TF Regression Code Along - Exploratory Data Analysis.mp4 143.6 MB
25. Neural Nets and Deep Learning/27. Keras Project Solutions - Data PreProcessing.mp4 131.0 MB
25. Neural Nets and Deep Learning/21. TF Classification - Dealing with Overfitting and Evaluation.srt 116.8 MB
25. Neural Nets and Deep Learning/21. TF Classification - Dealing with Overfitting and Evaluation.mp4 116.7 MB
25. Neural Nets and Deep Learning/25. Keras Project Solutions - Dealing with Missing Data - Part Two.mp4 101.5 MB
25. Neural Nets and Deep Learning/26. Keras Project Solutions - Categorical Data.mp4 89.5 MB
25. Neural Nets and Deep Learning/14. TF Syntax Basics - Part Two - Creating and Training the Model.mp4 88.4 MB
14. Introduction to Machine Learning/4. Evaluating Performance - Classification Error Metrics.mp4 86.7 MB
25. Neural Nets and Deep Learning/23. TensorFlow 2.0 Project Notebook Overview.mp4 84.4 MB
2. Environment Set-Up/1. Python Environment Setup.mp4 80.1 MB
25. Neural Nets and Deep Learning/17. TF Regression Code Along - Exploratory Data Analysis - Continued.mp4 79.9 MB
25. Neural Nets and Deep Learning/10. Cost Functions and Gradient Descent.mp4 79.7 MB
25. Neural Nets and Deep Learning/19. TF Regression Code Along - Model Evaluation and Predictions.mp4 72.3 MB
25. Neural Nets and Deep Learning/15. TF Syntax Basics - Part Three - Model Evaluation.mp4 67.9 MB
25. Neural Nets and Deep Learning/30. Keras Project Solutions - Model Evaluation.mp4 66.2 MB
26. Big Data and Spark with Python/7. EC2 Instance Set-Up.mp4 66.0 MB
25. Neural Nets and Deep Learning/8. Activation Functions.mp4 65.6 MB
26. Big Data and Spark with Python/9. PySpark Setup.mp4 63.3 MB

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【影视】 [FreeCourseSite.com] Udemy - Data Science and Machine Learning Bootcamp with R

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4. Mac OS Installation Set-Up/1. Mac OS Installation Procedure.mp4 74.9 MB
18. Capstone Data Project/2. Capstone Project Solutions Walkthrough.mp4 66.4 MB
19. Introduction to Machine Learning with R/2. Introduction to Machine Learning.mp4 62.6 MB
21. Machine Learning Project - Linear Regression/2. ML - Linear Regression Project - Solutions Part 1.mp4 62.4 MB
14. Data Manipulation with R/8. Guide to Using Tidyr.mp4 60.5 MB
15. Data Visualization with R/2. Histograms.mp4 59.7 MB
23. Machine Learning Project - Logistic Regression/2. Logistic Regression Project Solutions - Part 1.mp4 59.0 MB
20. Machine Learning with R - Linear Regression/2. Linear Regression with R - Part 1.mp4 58.3 MB
33. Machine Learning with R - Neural Nets/2. Neural Nets with R.mp4 57.4 MB
20. Machine Learning with R - Linear Regression/3. Linear Regression with R - Part 2.mp4 56.6 MB
22. Machine Learning with R - Logistic Regression/3. Logistic Regression with R - Part 2.mp4 49.9 MB
24. Machine Learning with R - K Nearest Neighbors/2. K Nearest Neighbors with R.mp4 49.0 MB
21. Machine Learning Project - Linear Regression/1. Introduction to Linear Regression Project.mp4 48.8 MB
22. Machine Learning with R - Logistic Regression/2. Logistic Regression with R - Part 1.mp4 48.6 MB
1. Course Introduction/4.1 R-Course-HTML-Notes.zip 47.8 MB
6. Development Environment Overview/2.1 R-Course-HTML-Notes.zip 47.8 MB
18. Capstone Data Project/1. Introduction to Capstone Project.mp4 47.7 MB
15. Data Visualization with R/3. Scatterplots.mp4 47.4 MB
12. R Programming Basics/10. Functions Training Exercise - Solutions.mp4 45.5 MB
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【影视】 [Udemy] Python for Data Science and Machine Learning Bootcamp (2020) [En]

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25. Neural Nets and Deep Learning/31. Tensorboard.mp4 151.2 MB
25. Neural Nets and Deep Learning/24. Keras Project Solutions - Dealing with Missing Data.mp4 150.6 MB
25. Neural Nets and Deep Learning/16. TF Regression Code Along - Exploratory Data Analysis.mp4 143.6 MB
25. Neural Nets and Deep Learning/27. Keras Project Solutions - Data PreProcessing.mp4 131.0 MB
25. Neural Nets and Deep Learning/21. TF Classification - Dealing with Overfitting and Evaluation.mp4 116.8 MB
25. Neural Nets and Deep Learning/25. Keras Project Solutions - Dealing with Missing Data - Part Two.mp4 101.5 MB
26. Big Data and Spark with Python/7. EC2 Instance Set-Up.mp4 90.7 MB
25. Neural Nets and Deep Learning/26. Keras Project Solutions - Categorical Data.mp4 89.5 MB
25. Neural Nets and Deep Learning/14. TF Syntax Basics - Part Two - Creating and Training the Model.mp4 88.4 MB
14. Introduction to Machine Learning/4. Evaluating Performance - Classification Error Metrics.mp4 86.7 MB
25. Neural Nets and Deep Learning/23. TensorFlow 2.0 Project Notebook Overview.mp4 84.4 MB
2. Environment Set-Up/1. Python Environment Setup.mp4 80.1 MB
25. Neural Nets and Deep Learning/17. TF Regression Code Along - Exploratory Data Analysis - Continued.mp4 79.9 MB
25. Neural Nets and Deep Learning/10. Cost Functions and Gradient Descent.mp4 79.7 MB
18. K Nearest Neighbors/4. KNN Project Solutions.mp4 74.3 MB
26. Big Data and Spark with Python/12. RDD Transformations and Actions.mp4 74.2 MB
26. Big Data and Spark with Python/9. PySpark Setup.mp4 74.1 MB
25. Neural Nets and Deep Learning/19. TF Regression Code Along - Model Evaluation and Predictions.mp4 72.3 MB
25. Neural Nets and Deep Learning/15. TF Syntax Basics - Part Three - Model Evaluation.mp4 67.9 MB
25. Neural Nets and Deep Learning/30. Keras Project Solutions - Model Evaluation.mp4 66.2 MB

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