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[ FreeCourseWeb.com ] Packt - scikit-learn Recipes.zip 498.8 MB
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- 【压缩文件】 Python 3 Advanced Computer Vision with OpenCV & Scikit-image
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1.Predicting the Wine Quality Using Multiple Linear Regression/04.Implementing the Solution.mp4 44.2 MB
2.Bike Sharing Demand Prediction Using Regression Trees/09.Feature Analysis and Engineering.mp4 41.1 MB
1.Predicting the Wine Quality Using Multiple Linear Regression/05.Evaluating and Improving the Model.mp4 40.7 MB
3.Heart Disease Predictions with Support Vector Machines/15.Implementing the Solution.mp4 31.0 MB
4.Poker Hand Predictions with K-Means Clustering/19.Feature Analysis and Engineering.mp4 30.1 MB
3.Heart Disease Predictions with Support Vector Machines/14.Feature Analysis and Engineering.mp4 28.9 MB
4.Poker Hand Predictions with K-Means Clustering/20.Implementing the Solution.mp4 27.6 MB
2.Bike Sharing Demand Prediction Using Regression Trees/10.Implementing the Solution.mp4 25.5 MB
5.Understanding Buying Behavior Using Hierarchical Clustering/25.Implementing the Solution.mp4 22.8 MB
4.Poker Hand Predictions with K-Means Clustering/21.Analyze the Results.mp4 22.7 MB
5.Understanding Buying Behavior Using Hierarchical Clustering/24.Feature Analysis and Engineering.mp4 22.6 MB
4.Poker Hand Predictions with K-Means Clustering/18.K-Means Clustering.mp4 19.3 MB
2.Bike Sharing Demand Prediction Using Regression Trees/08.Decision Trees and Random Forest.mp4 17.3 MB
2.Bike Sharing Demand Prediction Using Regression Trees/11.Analyze the Results.mp4 16.0 MB
5.Understanding Buying Behavior Using Hierarchical Clustering/26.Analyze the Results.mp4 15.2 MB
3.Heart Disease Predictions with Support Vector Machines/16.Analyze the Results.mp4 13.4 MB
1.Predicting the Wine Quality Using Multiple Linear Regression/06.Analyzing the Results.mp4 13.2 MB
1.Predicting the Wine Quality Using Multiple Linear Regression/03.Multiple Linear Regression.mp4 13.2 MB
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- 【压缩文件】 Artificial Intelligence #5 MLP Networks with Scikit & Keras
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Artificial Intelligence #5 MLP Networks with Scikit & Keras.zip 921.6 MB
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Working Files/Advanced_Machine_Learning_with_scikit_learn_Working_Files.zip 60.3 MB
02. Model Complexity, Overfitting And Underfitting/02_02-Linear Models InDepth.mp4 35.2 MB
01. Introduction/01_03-The Classifier Interface.mp4 28.5 MB
01. Introduction/01_11-How To Access Your Working Files.mp4 27.7 MB
07. Handling Text Data/07_03-Text Classification For Sentiment Analysis Part 1.mp4 26.6 MB
01. Introduction/01_06-The Cluster Interface.mp4 23.4 MB
02. Model Complexity, Overfitting And Underfitting/02_03-Kernel SVMs InDepth.mp4 22.9 MB
05. Model Selection For Unsupervised Learning/05_01-Guidelines For Unsupervised Model Selection.mp4 22.7 MB
04. Advanced Metrics And Imbalanced Classes/04_01-Be Mindful Of Default Metrics.mp4 21.6 MB
04. Advanced Metrics And Imbalanced Classes/04_04-Defining Custom Metrics.mp4 21.4 MB
01. Introduction/01_09-CrossValidation With Cross_Val_Score.mp4 21.3 MB
04. Advanced Metrics And Imbalanced Classes/04_03-AUC.mp4 20.6 MB
01. Introduction/01_10-Parameter Searches With GridSearchCV.mp4 20.3 MB
07. Handling Text Data/07_02-BagOfWords Representations.mp4 20.0 MB
03. Pipelines/03_02-Defining A Pipeline And Basic Usage.mp4 20.0 MB
06. Dealing With Categorical Variables, Dictionaries, And Incomplete Data/06_01-Why Real Data Is Messy.mp4 20.0 MB
08. Out Of Core Learning/08_05-Application OutOfCore Text Classification.mp4 19.3 MB
08. Out Of Core Learning/08_04-Subsample And Transform Supervised Transformations For Out Of Core Learning.mp4 19.2 MB
05. Model Selection For Unsupervised Learning/05_02-Model Selection For Density Models.mp4 19.0 MB
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05-Implement a Naive Bayes Classifier in Python and Scikit-learn to Categorize Text.mp4 16.9 MB
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5. Linear Regression - Practical Example/1. Practical Example (Part 1).mp4 101.8 MB
6. Logistic Regression/3. What is the Difference Between a Logistic and a Logit Function.mp4 79.5 MB
7. Cluster Analysis/17. What Can be Done with Cluster Analysis.mp4 66.6 MB
7. Cluster Analysis/2. Examples of Clustering.mp4 66.0 MB
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5. Linear Regression - Practical Example/8. Practical Example (Part 5).mp4 60.7 MB
5. Linear Regression - Practical Example/6. Practical Example (Part 4).mp4 58.7 MB
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3. Linear Regression with StatsModels/38. Dealing with Categorical Data.mp4 53.9 MB
3. Linear Regression with StatsModels/3. The Linear Regression Model.mp4 53.5 MB
7. Cluster Analysis/16. Practical Example Market Segmentation (Part 2).mp4 53.3 MB
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4. Linear Regression with Sklearn/19. Training and Testing.mp4 51.6 MB
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5. Linear Regression - Practical Example/2. Practical Example (Part 2).mp4 48.2 MB
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5. Linear Regression - Practical Example/1. Practical Example (Part 1).mp4 101.8 MB
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5. Linear Regression - Practical Example/8. Practical Example (Part 5).mp4 60.7 MB
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3. Linear Regression with StatsModels/3. The Linear Regression Model.mp4 53.5 MB
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5. Linear Regression - Practical Example/2. Practical Example (Part 2).mp4 48.2 MB
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~Get Your Files Here !/2. Scaling Data Part 1.mp4 136.4 MB
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~Get Your Files Here !/4. Dealing with Categorical Variables.mp4 107.8 MB
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~Get Your Files Here !/2. Linear Regression in scikit-learn.mp4 173.7 MB
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