├── LICENSE ├── README.md ├── Section 1 ├── Video 1.1 Improving your models using Feature engineering.ipynb ├── Video 1.2 Implementing feature engineering with logistic regression.ipynb ├── Video 1.3 Extracting data with feature selection and interaction.ipynb ├── video 1.4 Combining all together.ipynb └── video 1.5 Build model based on real-world problem.ipynb ├── Section 2 ├── video 2.1 Support Vector Machines.ipynb ├── video 2.2 Implementing kNN on the dataset.ipynb ├── video 2.3 Decision Tree as predictive model.ipynb ├── video 2.4 Tricks with dimensionality reduction method.ipynb └── video 2.5 combining all together.ipynb ├── Section 3 ├── 3.1 Random Forest for classification.ipynb ├── 3.2 Gradient boosting trees and bayes optimization.ipynb ├── 3.2 gradient boosting.ipynb ├── 3.4 Implement blending.ipynb └── 3.5 stacking.ipynb ├── Section 4 ├── 4_1_Memory based collaborative filtering.ipynb ├── 4_2_Item to item recommendation with kNN.ipynb ├── 4_3_Applying Matrix Factorization on dataset.ipynb └── 4_4_Wordbach at use.ipynb └── Section 5 ├── 5_1_Validation dataset tuning.ipynb ├── 5_2_Regularizing model to avoid overfitting.ipynb ├── 5_3_Adversarial Validation.ipynb └── 5_4_Perform metric selection on real data.ipynb /LICENSE: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Python-Machine-Learning-Tips-Tricks-and-Techniques/HEAD/LICENSE -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Python-Machine-Learning-Tips-Tricks-and-Techniques/HEAD/README.md -------------------------------------------------------------------------------- /Section 1/Video 1.1 Improving your models using Feature engineering.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Python-Machine-Learning-Tips-Tricks-and-Techniques/HEAD/Section 1/Video 1.1 Improving your models using Feature engineering.ipynb -------------------------------------------------------------------------------- /Section 1/Video 1.2 Implementing feature engineering with logistic regression.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Python-Machine-Learning-Tips-Tricks-and-Techniques/HEAD/Section 1/Video 1.2 Implementing feature engineering with logistic regression.ipynb -------------------------------------------------------------------------------- /Section 1/Video 1.3 Extracting data with feature selection and interaction.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Python-Machine-Learning-Tips-Tricks-and-Techniques/HEAD/Section 1/Video 1.3 Extracting data with feature selection and interaction.ipynb -------------------------------------------------------------------------------- /Section 1/video 1.4 Combining all together.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Python-Machine-Learning-Tips-Tricks-and-Techniques/HEAD/Section 1/video 1.4 Combining all together.ipynb -------------------------------------------------------------------------------- /Section 1/video 1.5 Build model based on real-world problem.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Python-Machine-Learning-Tips-Tricks-and-Techniques/HEAD/Section 1/video 1.5 Build model based on real-world problem.ipynb -------------------------------------------------------------------------------- /Section 2/video 2.1 Support Vector Machines.ipynb: 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model.ipynb -------------------------------------------------------------------------------- /Section 2/video 2.4 Tricks with dimensionality reduction method.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Python-Machine-Learning-Tips-Tricks-and-Techniques/HEAD/Section 2/video 2.4 Tricks with dimensionality reduction method.ipynb -------------------------------------------------------------------------------- /Section 2/video 2.5 combining all together.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/PacktPublishing/Python-Machine-Learning-Tips-Tricks-and-Techniques/HEAD/Section 2/video 2.5 combining all together.ipynb -------------------------------------------------------------------------------- /Section 3/3.1 Random Forest for classification.ipynb: 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