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【影视】 [FreeCourseSite.com] Udemy - 2021 Python for Machine Learning & Data Science Masterclass

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5. Pandas/28. Pandas Project Exercise Solutions.mp4 190.4 MB
8. Data Analysis and Visualization Capstone Project Exercise/4. Capstone Project Solutions - Part Three.mp4 150.9 MB
5. Pandas/26. Pandas Pivot Tables.mp4 135.0 MB
7. Seaborn Data Visualizations/2. Scatterplots with Seaborn.mp4 134.9 MB
6. Matplotlib/11. Matplotlib Exercise Questions - Solutions.mp4 129.1 MB
8. Data Analysis and Visualization Capstone Project Exercise/2. Capstone Project Solutions - Part One.mp4 122.6 MB
5. Pandas/4. DataFrames - Part One - Creating a DataFrame.mp4 119.6 MB
7. Seaborn Data Visualizations/8. Categorical Plots - Distributions within Categories - Coding with Seaborn.mp4 116.6 MB
8. Data Analysis and Visualization Capstone Project Exercise/3. Capstone Project Solutions - Part Two.mp4 116.4 MB
7. Seaborn Data Visualizations/14. Seaborn Plot Exercises Solutions.mp4 116.0 MB
4. NumPy/2. NumPy Arrays.mp4 115.0 MB
5. Pandas/23. Pandas Input and Output - HTML Tables.mp4 111.8 MB
5. Pandas/15. GroupBy Operations - Part Two - MultiIndex.mp4 111.0 MB
5. Pandas/25. Pandas Input and Output - SQL Databases.mp4 108.2 MB
5. Pandas/21. Pandas - Time Methods for Date and Time Data.mp4 106.9 MB
10. Linear Regression/24. L1 Regularization - Lasso Regression - Background and Implementation.mp4 104.9 MB
1. Introduction to Course/3. Anaconda Python and Jupyter Install and Setup.mp4 103.6 MB
5. Pandas/10. Pandas - Useful Methods - Apply on Multiple Columns.mp4 103.3 MB
5. Pandas/13. Missing Data - Pandas Operations.mp4 102.6 MB
5. Pandas/7. DataFrames - Part Four - Working with Rows.mp4 101.4 MB

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【影视】 [FreeCourseSite.com] Udemy - Master Deep Learning with TensorFlow in Python

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14. Appendix Linear Algebra Fundamentals/11. Why is Linear Algebra Useful.mp4 151.3 MB
1. Welcome! Course introduction/1. Meet your instructors and why you should study machine learning.mp4 110.9 MB
14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.mp4 52.2 MB
14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.mp4 51.8 MB
2. Introduction to neural networks/24. N-parameter gradient descent.mp4 41.4 MB
2. Introduction to neural networks/12. The linear model. Multiple inputs and multiple outputs.mp4 40.1 MB
14. Appendix Linear Algebra Fundamentals/8. Transpose of a Matrix.mp4 39.9 MB
13. Business case/4. Preprocessing the data.mp4 36.0 MB
14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.mp4 35.5 MB
14. Appendix Linear Algebra Fundamentals/1. What is a Matrix.mp4 35.2 MB
14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.mp4 34.2 MB
13. Business case/6. Create a class for batching.mp4 29.0 MB
14. Appendix Linear Algebra Fundamentals/4. Scalars, Vectors and Matrices in Python.mp4 28.0 MB
14. Appendix Linear Algebra Fundamentals/9. Dot Product of Vectors.mp4 25.2 MB
13. Business case/1. Exploring the dataset and identifying predictors.mp4 24.4 MB
14. Appendix Linear Algebra Fundamentals/5. Tensors.mp4 23.6 MB
12. The MNIST example/9. Discuss the results and test.mp4 23.0 MB
4. Minimal example - your first machine learning algorithm/4. Minimal example - part 4.mp4 21.8 MB
13. Business case/7. Outlining the model.mp4 20.4 MB
12. The MNIST example/4. Outlining the model.mp4 19.3 MB

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【影视】 2020 AWS SageMaker, AI and Machine Learning - With Python

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2020 AWS SageMaker, AI and Machine Learning - With Python/11 E9 SageMaker HyperParameter Tuning/104 Lab Tuning Movie Rating Factorization Machine Recommender System.mp4 161.5 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/09 SageMaker - DeepAR Time Series Forecasting/085 Demo - Bike Rental as Time Series Forecasting Problem.mp4 110.1 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/03 E9 Machine Learning Concepts/019 E9 Data Types - How to handle mixed data types.mp4 106.9 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/04 E9.7 Model Performance Evaluation/033 Multiclass Classifier.mp4 104.8 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/05 2020 SageMaker Service Overview/037 DataFormat.mp4 97.7 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/08 SageMaker - Factorization Machines/078 Demo - Movie Recommender Data Preparation.mp4 95.1 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/09 SageMaker - DeepAR Time Series Forecasting/083 DeepAR Training and Inference Formats.mp4 93.8 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/04 E9.7 Model Performance Evaluation/025 Regression Model Performance.mp4 91.1 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/03 E9 Machine Learning Concepts/020 E9 Introduction to Python Notebook Environment.mp4 89.7 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/12 2020 Artificial Intelligence (AI) Services/118 7. Amazon Rekognition.mp4 89.0 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/01 Introduction and Housekeeping/008 2020 Configure IAM Users Setup Command Line Interface (CLI).mp4 88.7 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/10 E9 Integration Options for Model Endpoint/101 Microservice - API Gateway Lambda to Endpoint.mp4 88.2 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/06 E9 XGBoost - Gradient Boosted Trees/044 E9 Lab - Training Simple Regression.mp4 87.7 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/03 E9 Machine Learning Concepts/021 E9 Introduction to working with Missing Data.mp4 85.7 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/09 SageMaker - DeepAR Time Series Forecasting/086 Demo - Bike Rental Model Training.mp4 81.0 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/10 E9 Integration Options for Model Endpoint/097 Client to Endpoint using SageMaker SDK.mp4 80.7 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/09 SageMaker - DeepAR Time Series Forecasting/082 Introduction to DeepAR Time Series Forecasting.mp4 79.5 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/10 E9 Integration Options for Model Endpoint/100 Microservice - Lambda to Endpoint.mp4 77.8 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/15 2020 Storage for Servers/156 2020 Elastic Block Store (EBS).mp4 77.4 MB
2020 AWS SageMaker, AI and Machine Learning - With Python/01 Introduction and Housekeeping/003 2020 - Overview - AWS Machine Learning Specialty Exam.mp4 73.6 MB

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【影视】 [FreeCourseSite.com] Udemy - Bayesian Machine Learning in Python AB Testing

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8. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 195.5 MB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
5. Bayesian AB Testing/16. Bayesian Bandits Thompson Sampling Theory (pt 2).mp4 78.5 MB
4. Traditional AB Testing/14. Z-Test Code (pt 1).mp4 71.2 MB
5. Bayesian AB Testing/15. Bayesian Bandits Thompson Sampling Theory (pt 1).mp4 58.9 MB
5. Bayesian AB Testing/12. UCB1 Theory.mp4 58.5 MB
2. The High-Level Picture/2. What is Bayesian Machine Learning.mp4 57.3 MB
3. Bayes Rule and Probability Review/11. Probability Review in Code.mp4 57.0 MB
5. Bayesian AB Testing/1. Section Introduction The Explore-Exploit Dilemma.mp4 54.8 MB
5. Bayesian AB Testing/24. (Optional) Alternative Bandit Designs.mp4 54.5 MB
4. Traditional AB Testing/9. Hypothesis Testing - The API Approach.mp4 50.5 MB
7. Practice Makes Perfect/3. The most important quiz of all - Obtaining an infinite amount of practice.mp4 49.4 MB
5. Bayesian AB Testing/2. Applications of the Explore-Exploit Dilemma.srt 49.4 MB
5. Bayesian AB Testing/2. Applications of the Explore-Exploit Dilemma.mp4 49.3 MB
5. Bayesian AB Testing/19. Thompson Sampling With Gaussian Reward Theory.mp4 49.2 MB
4. Traditional AB Testing/17. Classical AB Testing Section Summary.mp4 48.5 MB
5. Bayesian AB Testing/8. Comparing Different Epsilons.mp4 46.1 MB
8. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
1. Introduction and Outline/3. How to succeed in this course.mp4 45.9 MB
3. Bayes Rule and Probability Review/6. Maximum Likelihood Estimation - Bernoulli.mp4 45.9 MB

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【影视】 Cluster Analysis & Unsupervised Machine Learning in R

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[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/9. Applied Example unsupervised K-means learning for mapping applications/2. Import images and their visualization in Earth Engine.mp4 148.8 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/2. Software used in this course/5. Interface of Google Earth Engine Code Editor & Explorer.mp4 133.3 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/5. Unsupervised Learning K-Means Clustering/3. K-means clustering Application to email marketing.mp4 116.1 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/9. Applied Example unsupervised K-means learning for mapping applications/3. Unsupervised K-means satellite image analysis in Earth Engine for mapping.mp4 108.7 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/6. More Unsupervised Clustering techniques Hands-On/1. Starting with Fuzzy K-means in R.mp4 107.1 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/5. Unsupervised Learning K-Means Clustering/5. Model-based Unsupervised Clustering in R.mp4 78.2 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/8. Independent Project in Cluster Analysis based on Case Study/2. Project Assignment.mp4 71.6 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/9. Applied Example unsupervised K-means learning for mapping applications/1. Understanding using satellite images for mapping tasks short introduction.mp4 66.4 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/6. More Unsupervised Clustering techniques Hands-On/2. Entropy Weighted K-Means in R.mp4 64.9 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/7. Performance Evaluation of Unsupervised Learning Clustering Algorithms in R/2. Selecting the number of clusters for unsupervised Clustering methods (K-Means).mp4 62.2 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/8. Independent Project in Cluster Analysis based on Case Study/1. Introduction to Case Study.mp4 60.9 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/3. R Crash Course - get started with R-programming in R-Studio/5. Lab data types and data structures in R.mp4 50.4 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/2. Software used in this course/3. Lab Get started with R in RStudio.mp4 50.0 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/1. Introduction/2. What is Machine Leraning and it's main types.mp4 49.1 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/2. Software used in this course/4. Sign up for Google Earth Engine (needed for your projects later in the course).mp4 47.9 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/7. Performance Evaluation of Unsupervised Learning Clustering Algorithms in R/1. How to assess a Clustering Tendency of the dataset.mp4 44.4 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/2. Software used in this course/2. How to install R and RStudio in 2020.mp4 40.6 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/7. Performance Evaluation of Unsupervised Learning Clustering Algorithms in R/3. Assessing the performance of unsupervised learning (clustering) algorithms.mp4 40.3 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/3. R Crash Course - get started with R-programming in R-Studio/7. Functions in R - overview.mp4 34.8 MB
[TutsNode.com] - Cluster Analysis & Unsupervised Machine Learning in R/3. R Crash Course - get started with R-programming in R-Studio/10. Read Data into R.mp4 33.5 MB

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

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18. Capstone Data Project/2. Capstone Project Solutions Walkthrough.mp4 57.1 MB
19. Introduction to Machine Learning with R/2. Introduction to Machine Learning.mp4 50.9 MB
21. Machine Learning Project - Linear Regression/2. ML - Linear Regression Project - Solutions Part 1.mp4 50.1 MB
23. Machine Learning Project - Logistic Regression/2. Logistic Regression Project Solutions - Part 1.mp4 49.7 MB
14. Data Manipulation with R/8. Guide to Using Tidyr.mp4 49.4 MB
20. Machine Learning with R - Linear Regression/2. Linear Regression with R - Part 1.mp4 49.2 MB
33. Machine Learning with R - Neural Nets/2. Neural Nets with R.mp4 48.5 MB
20. Machine Learning with R - Linear Regression/3. Linear Regression with R - Part 2.mp4 48.2 MB
15. Data Visualization with R/2. Histograms.mp4 47.8 MB
6. Development Environment Overview/2.1 R-Course-HTML-Notes.zip.zip 47.8 MB
1. Course Introduction/4.1 R-Course-HTML-Notes.zip.zip 47.8 MB
22. Machine Learning with R - Logistic Regression/3. Logistic Regression with R - Part 2.mp4 42.9 MB
24. Machine Learning with R - K Nearest Neighbors/2. K Nearest Neighbors with R.mp4 42.4 MB
22. Machine Learning with R - Logistic Regression/2. Logistic Regression with R - Part 1.mp4 41.5 MB
15. Data Visualization with R/3. Scatterplots.mp4 39.4 MB
12. R Programming Basics/10. Functions Training Exercise - Solutions.mp4 38.5 MB
32. Machine Learning with R - Natural Language Processing/3. Natural Language Processing with R - Part 2.mp4 37.4 MB
12. R Programming Basics/8. Functions.mp4 36.8 MB
18. Capstone Data Project/1. Introduction to Capstone Project.mp4 36.6 MB
9. R Data Frames/5. Overview of Data Frame Operations - Part 2.mp4 35.8 MB

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【影视】 [FreeCoursesOnline.Me] Linkedin - PyTorch Essential Training Deep Learning

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03 - Working with Classes and Tensors/01 - Classes.mp4 51.3 MB
04 - Working with Loss, Autograd, and Optimizers/01 - Loss.mp4 43.4 MB
02 - Fashion MNIST and Neural Networks/01 - Working with the Fashion MNIST dataset.mp4 34.8 MB
05 - Troubleshooting and CPUGPU Usage/02 - CPU to GPU.mp4 15.5 MB
06 - Conclusion/01 - Future project ideas.mp4 15.1 MB
05 - Troubleshooting and CPUGPU Usage/01 - Troubleshooting.mp4 12.0 MB
04 - Working with Loss, Autograd, and Optimizers/02 - Autograd.mp4 11.3 MB
02 - Fashion MNIST and Neural Networks/02 - Neural network intuition.mp4 11.1 MB
04 - Working with Loss, Autograd, and Optimizers/05 - Using optimizers.mp4 10.5 MB
01 - Introduction/01 - Welcome.mp4 9.9 MB
04 - Working with Loss, Autograd, and Optimizers/03 - Autograd with tensors.mp4 9.4 MB
05 - Troubleshooting and CPUGPU Usage/03 - Validation.mp4 8.1 MB
03 - Working with Classes and Tensors/02 - Tensors.mp4 7.6 MB
03 - Working with Classes and Tensors/03 - Training the network.mp4 5.9 MB
01 - Introduction/02 - What you should know before watching this course.mp4 4.0 MB
04 - Working with Loss, Autograd, and Optimizers/04 - Optimizers.mp4 3.0 MB
Exercise Files/Ex_Files_PyTorch_EssT_DL.zip 53.1 kB
05 - Troubleshooting and CPUGPU Usage/02 - CPU to GPU.srt 9.3 kB
02 - Fashion MNIST and Neural Networks/02 - Neural network intuition.srt 9.1 kB
04 - Working with Loss, Autograd, and Optimizers/01 - Loss.srt 8.5 kB

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【影视】 Lynda - Learning Bash Scripting [AhLaN]

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3 - 2. Building Bash Scripts/17 - Coloring and styling text.mp4 17.0 MB
2 - 1. Working with the Command Line/08 - Manipulating output with grep, awk, and cut.mp4 16.0 MB
2 - 1. Working with the Command Line/05 - Reviewing common Bash commands.mp4 14.7 MB
2 - 1. Working with the Command Line/06 - Tilde and brace expansion.mp4 11.9 MB
3 - 2. Building Bash Scripts/23 - Solution - Make a script that generates a system report.mp4 11.7 MB
2 - 1. Working with the Command Line/07 - Changing where things go with pipes and redirection.mp4 10.9 MB
3 - 2. Building Bash Scripts/18 - Exploring some handy helpers - date and printf.mp4 9.3 MB
5 - 4. Interacting with the User/32 - Ensuring a response.mp4 8.7 MB
4 - 3. Control Structures/26 - Introducing for loops.mp4 8.7 MB
3 - 2. Building Bash Scripts/15 - Comparing values.mp4 8.3 MB
5 - 4. Interacting with the User/31 - Getting input during execution.mp4 7.7 MB
1 - Introduction/02 - What you need to know before continuing.mp4 7.7 MB
3 - 2. Building Bash Scripts/16 - Working with strings.mp4 7.6 MB
3 - 2. Building Bash Scripts/19 - Working with arrays.mp4 7.0 MB
4 - 3. Control Structures/24 - Testing truth conditions with the if keyword.mp4 6.9 MB
3 - 2. Building Bash Scripts/12 - Working with variables.mp4 6.6 MB
3 - 2. Building Bash Scripts/14 - Working with numbers.mp4 6.4 MB
3 - 2. Building Bash Scripts/20 - Reading and writing text files.mp4 6.4 MB
2 - 1. Working with the Command Line/04 - What's Bash.mp4 6.3 MB
4 - 3. Control Structures/28 - Using functions.mp4 6.3 MB

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【影视】 2021 Python for Data Science & Machine Learning from A-Z

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[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/19. PCA/7. PCA - Image Compression.mp4 262.1 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/16. Ensemble Learning and Random Forests/6. Implementing Random Forests from scratch Part 1.mp4 212.4 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/15. Decision Trees/7. ID3 - Putting Everything Together.mp4 191.3 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/14. K Nearest Neighbors/3. EDA on Iris Dataset.mp4 169.7 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/15. Decision Trees/3. What is Entropy and Information Gain.mp4 142.7 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/19. PCA/9. PCA - Biplot and the Screen Plot.mp4 142.2 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/1. Introduction/6. How To Get a Data Science Job.mp4 137.6 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/1. Introduction/5. What is a Data Scientist.mp4 133.7 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/17. Support Vector Machines/6. SVM - Kernel Types.mp4 132.5 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/15. Decision Trees/2. EDA on Adult Dataset.mp4 129.2 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/15. Decision Trees/8. Evaluating our ID3 implementation.mp4 127.9 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/19. PCA/8. PCA Data Preprocessing.mp4 126.3 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/15. Decision Trees/13. Pruning.mp4 118.5 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/17. Support Vector Machines/8. SVM with Non-linear Dataset.mp4 117.0 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/13. Linear and Logistic Regression/3. Linear Regression + Correlation Methods.mp4 115.7 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/18. K-means/3. Representing Clusters.mp4 114.9 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/3. Python For Data Science/15. Python Dictionaries.mp4 109.2 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/17. Support Vector Machines/7. SVM with Linear Dataset (Iris).mp4 106.5 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/18. K-means/1. Unsupervised Machine Learning Intro.mp4 105.8 MB
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z/9. Machine Learning/1. Introduction To Machine Learning.mp4 103.5 MB

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【影视】 [FTUForum.com] [UDEMY] Python Machine Learning Basics Shallow Learning Algorithms [FTU]

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2. Machine Learning Framework/4. MI Python skeleton.mp4 61.5 MB
3. SVD/1. SVD implementation.mp4 55.6 MB
5. Going Live/3. Surpriselib and Flask.mp4 50.9 MB
2. Machine Learning Framework/1. Scikit Surprise.mp4 40.4 MB
4. KNN/1. KNN implementation.mp4 39.5 MB
3. SVD/2. SVD Theory.mp4 38.8 MB
5. Going Live/1. Display KNN neighbors.mp4 33.2 MB
1. Introduction/1. What is Machine Learning.mp4 30.1 MB
4. KNN/2. Knn theory.mp4 23.7 MB
5. Going Live/2. Display SVD Item Predictions.mp4 23.7 MB
2. Machine Learning Framework/2. Evaluation.mp4 22.6 MB
4. KNN/3. User vs Item.mp4 19.5 MB
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1. Introduction/3. Theory vs Practice.mp4 12.0 MB
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【影视】 Machine Learning Basics Practical Linear Regression in R

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[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/4. More types of linear regression models in R/6. GLM Preview Logistic Regression Model & Accuracy Assessment.mp4 86.9 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/4. More types of linear regression models in R/1. Lab Multiple linear regression - model estimation in R.mp4 63.1 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/4. More types of linear regression models in R/5. ANOVA - Categorical variables with more than two levels in linear regressions.mp4 57.2 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/3. Linear Regression in R/2. Lab your first linear regression model.mp4 55.9 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/1. Introduction/2. Introduction to Regression Analysis and Linear Regression.mp4 51.5 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/2. Software used in this course R-Studio and Introduction to R/3. Lab Get started with R in RStudio.mp4 50.0 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/1. Introduction/4. What is Machine Leraning and it's main types.mp4 49.1 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/4. More types of linear regression models in R/3. Lab Multiple linear regression with interaction in R.mp4 46.7 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/3. Linear Regression in R/5. Linear Regression Diagnostics.mp4 45.3 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/2. Software used in this course R-Studio and Introduction to R/2. How to install R and RStudio in 2020.mp4 40.6 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/4. More types of linear regression models in R/8. Lab Receiver operating characteristic (ROC) curve and AUC.mp4 38.5 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/3. Linear Regression in R/9. Prediction model evaluation with data split out-of-sample RMSE.mp4 32.7 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/4. More types of linear regression models in R/4. Lab Regression with Categorical Variables Dummy Coding Essentials in R.mp4 31.1 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/3. Linear Regression in R/8. Lab Predict with linear regression model & RMSE as in-sample error.mp4 25.5 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/4. More types of linear regression models in R/2. Lab Multiple linear regression - prediction in R.mp4 19.8 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/1. Introduction/1. Introduction.mp4 18.1 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/3. Linear Regression in R/1. Getting started with linear regression.mp4 16.9 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/3. Linear Regression in R/3. Correlation in Regression Analysis in R Lab.mp4 13.7 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/2. Software used in this course R-Studio and Introduction to R/1. What is R and RStudio.mp4 12.8 MB
[TutsNode.com] - Machine Learning Basics Practical Linear Regression in R/3. Linear Regression in R/4. How to know if the model is best fit for your data - An overview.mp4 9.6 MB

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03.Technical and Managerial Roles/0302.Pushing your client.mp4 27.8 MB
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04.Leader and Follower Roles/0401.Applying the roles to stakeholders.mp4 23.0 MB
06.Conclusion/0602.Exercise The final interview.mp4 23.0 MB
02.The Consultant's Job and Roles They Play/0204.Assessing the required roles.mp4 22.7 MB
04.Leader and Follower Roles/0402.Influencing as a leader and follower.mp4 22.5 MB
02.The Consultant's Job and Roles They Play/0202.The consulting attitude.mp4 22.5 MB
04.Leader and Follower Roles/0405.Exercise solution Applying the roles.mp4 22.4 MB
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02.The Consultant's Job and Roles They Play/0206.Exercise solution The initial interview.mp4 22.1 MB
03.Technical and Managerial Roles/0303.Assessing your effectiveness with these roles.mp4 22.1 MB
04.Leader and Follower Roles/0404.Exercise Applying the roles.mp4 20.0 MB
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【影视】 GetFreeCourses.Me-Udemy-Cutting-Edge AI Deep Reinforcement Learning in Python

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6. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4 203.8 MB
4. DDPG (Deep Deterministic Policy Gradient)/5. DDPG Code (part 1).mp4 203.0 MB
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6. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 175.1 MB
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6. Appendix FAQ/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 123.2 MB
4. DDPG (Deep Deterministic Policy Gradient)/4. MuJoCo.mp4 115.8 MB
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6. Appendix FAQ/10. What order should I take your courses in (part 1).mp4 104.2 MB
3. A2C (Advantage Actor-Critic)/2. A2C Theory (part 1).mp4 100.9 MB
6. Appendix FAQ/6. How to Code by Yourself (part 1).mp4 86.6 MB
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2. Review of Fundamental Reinforcement Learning Concepts/5. Temporal Difference Learning (TD).mp4 82.4 MB
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【影视】 Lynda.com - Learning ECMAScript 6 (2017 ENG)

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02. Transpiling ES6/02_04. Migrating to webpack 3.mp4 20.7 MB
02. Transpiling ES6/02_03. Transpiling with webpack.mp4 19.9 MB
05. Asynchronous Features/05_01. Intro to promises.mp4 19.8 MB
04. ES6 Functions and Objects/04_06. Generators.mp4 19.6 MB
05. Asynchronous Features/05_03. Loading Data with Fetch.mp4 18.2 MB
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06. ES6 Classes/06_03. Getters and setters.mp4 15.0 MB
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05. Asynchronous Features/05_05. Async with fetch.mp4 14.1 MB
04. ES6 Functions and Objects/04_04. Arrow functions and the THIS scope.mp4 14.0 MB
03. ES6 Syntax/03_03. Template strings.mp4 13.7 MB
05. Asynchronous Features/05_04. Async and await.mp4 13.7 MB
05. Asynchronous Features/05_02. Building promises.mp4 13.0 MB
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【影视】 [DesireCourse.Net] Udemy - Bayesian Machine Learning in Python AB Testing

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7. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.mp4 195.5 MB
8. Extra Help With Python Coding for Beginners/3. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
4. Traditional AB Testing/9. CTR AB Test in Code.mp4 59.7 MB
2. The High-Level Picture/2. What is Bayesian Machine Learning.mp4 57.3 MB
6. Practice Makes Perfect/6. The most important quiz of all - Obtaining an infinite amount of practice.mp4 52.4 MB
7. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
3. Bayes Rule and Probability Review/6. Maximum Likelihood Estimation - Bernoulli.mp4 45.9 MB
5. Bayesian AB Testing/2. More about the Explore-Exploit Dilemma.mp4 45.9 MB
3. Bayes Rule and Probability Review/3. Calculating Probabilities - Practice.mp4 43.8 MB
3. Bayes Rule and Probability Review/8. Maximum Likelihood Estimation - Gaussian (pt 1).mp4 42.9 MB
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9. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).mp4 39.5 MB
3. Bayes Rule and Probability Review/9. Maximum Likelihood Estimation - Gaussian (pt 2).mp4 33.6 MB
1. Introduction and Outline/2. Where to get the code for this course.mp4 31.9 MB
9. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).mp4 30.8 MB
1. Introduction and Outline/1. What's this course all about.mp4 30.7 MB
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6. Linear Regression/18. Ridge regression and Lasso in Python.mp4 164.2 MB
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5. Data Preprocessing/16. Bi-variate analysis and Variable transformation.mp4 119.3 MB
6. Linear Regression/3. Assessing accuracy of predicted coefficients.mp4 109.5 MB
6. Linear Regression/10. Multiple Linear Regression in Python.mp4 92.4 MB
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2. Basics of Statistics/3. Describing data Graphically.mp4 86.2 MB
5. Data Preprocessing/23. Correlation Analysis.mp4 85.2 MB
3. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4 84.6 MB
6. Linear Regression/5. Simple Linear Regression in Python.vtt 82.5 MB
6. Linear Regression/5. Simple Linear Regression in Python.mp4 82.5 MB
5. Data Preprocessing/3. The Dataset and the Data Dictionary.mp4 82.4 MB
5. Data Preprocessing/7. EDD in Python.mp4 78.7 MB
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