├── Notebook I Linear Regression.ipynb ├── Notebook II Logistic Regression.ipynb ├── Notebook III Decision Trees.ipynb ├── Notebook IV Bootstrap.ipynb ├── Notebook IX PCA.ipynb ├── Notebook V Bagging.ipynb ├── Notebook VI Random Forest.ipynb ├── Notebook VII Boosting.ipynb ├── Notebook VIII Boosting Classification.ipynb ├── Notebook X Adaboost Classification.ipynb ├── Notebook XI Adaboost Regression.ipynb ├── Notebook XII Gradient Boost Regression.ipynb ├── Notebook XIII KNN.ipynb ├── Notebook XIV Pandas Data Pipelines.ipynb ├── Notebook XIX Perceptron.ipynb ├── Notebook XV KNN Recommender System.ipynb ├── Notebook XVI Decision Trees with Missing Values.ipynb ├── Notebook XVII Decision Trees with Categorical Features.ipynb ├── Notebook XVIII K-Means.ipynb ├── Notebook XX Batch Gradient Descent.ipynb ├── Notebook XXI Stochastic Gradient Descent.ipynb ├── Notebook XXII Mini-Batch Gradient Descent.ipynb ├── Notebook XXIII What is a Sklearn Pipeline?.ipynb ├── Notebook XXIV Multilayer Perceptron Regressor in Numpy from Scratch.ipynb ├── Notebook XXIX Learn the PageRank Algorithm with 1 Simple Example.ipynb ├── Notebook XXV Multilayer Perceptron Classifier in Numpy from Scratch.ipynb ├── Notebook XXVI Pyspark Pipeline.ipynb ├── Notebook XXVII Custom Pyspark Transformers.ipynb ├── Notebook XXVIII Custom Pyspark Estimators.ipynb ├── Notebook XXX The Weighted PageRank Algorithm.ipynb ├── Notebook XXXI Breadth First Search Algorithm.ipynb ├── Notebook XXXII Calculating Max Flow.ipynb ├── Notebook XXXIII Shapley Values for Machine Learning.ipynb ├── Notebook XXXIV Area Under the Curve.ipynb ├── Notebook XXXV 3 Methods for Hyperparameter Tuning with Random Forest.ipynb ├── Notebook XXXVI Global Explainability in Machine Learning.ipynb ├── README.md ├── [Video] 3 Methods for Hyperparameter Tuning with XGBoost.ipynb ├── [Video] Dangling Nodes in PageRank.ipynb ├── [Video] Introduction to Shapley Values.ipynb ├── [Video] PCA_Biplot.ipynb ├── [Video] Personalized PageRank.ipynb ├── [Video] xgboost vs lightgbm vs catboost vs adaboost vs gbm.ipynb └── decisiontrees ├── __init__.py ├── abstract └── base_tree.py ├── treeclassifier.py └── treeregressor.py /Notebook I Linear Regression.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook I Linear Regression.ipynb -------------------------------------------------------------------------------- /Notebook II Logistic Regression.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook II Logistic Regression.ipynb -------------------------------------------------------------------------------- /Notebook III Decision Trees.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook III Decision Trees.ipynb -------------------------------------------------------------------------------- /Notebook IV Bootstrap.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook IV Bootstrap.ipynb -------------------------------------------------------------------------------- /Notebook IX PCA.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook IX PCA.ipynb -------------------------------------------------------------------------------- /Notebook V Bagging.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook V Bagging.ipynb -------------------------------------------------------------------------------- /Notebook VI Random Forest.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook VI Random Forest.ipynb -------------------------------------------------------------------------------- /Notebook VII Boosting.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook VII Boosting.ipynb -------------------------------------------------------------------------------- /Notebook VIII Boosting Classification.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook VIII Boosting Classification.ipynb -------------------------------------------------------------------------------- /Notebook X Adaboost Classification.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook X Adaboost Classification.ipynb -------------------------------------------------------------------------------- /Notebook XI Adaboost Regression.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XI Adaboost Regression.ipynb -------------------------------------------------------------------------------- /Notebook XII Gradient Boost Regression.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XII Gradient Boost Regression.ipynb -------------------------------------------------------------------------------- /Notebook XIII KNN.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XIII KNN.ipynb -------------------------------------------------------------------------------- /Notebook XIV Pandas Data Pipelines.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XIV Pandas Data Pipelines.ipynb -------------------------------------------------------------------------------- /Notebook XIX Perceptron.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XIX Perceptron.ipynb -------------------------------------------------------------------------------- /Notebook XV KNN Recommender System.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XV KNN Recommender System.ipynb -------------------------------------------------------------------------------- /Notebook XVI Decision Trees with Missing Values.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XVI Decision Trees with Missing Values.ipynb -------------------------------------------------------------------------------- /Notebook XVII Decision Trees with Categorical Features.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XVII Decision Trees with Categorical Features.ipynb -------------------------------------------------------------------------------- /Notebook XVIII K-Means.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XVIII K-Means.ipynb -------------------------------------------------------------------------------- /Notebook XX Batch Gradient Descent.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XX Batch Gradient Descent.ipynb -------------------------------------------------------------------------------- /Notebook XXI Stochastic Gradient Descent.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXI Stochastic Gradient Descent.ipynb -------------------------------------------------------------------------------- /Notebook XXII Mini-Batch Gradient Descent.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXII Mini-Batch Gradient Descent.ipynb -------------------------------------------------------------------------------- /Notebook XXIII What is a Sklearn Pipeline?.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXIII What is a Sklearn Pipeline?.ipynb -------------------------------------------------------------------------------- /Notebook XXIV Multilayer Perceptron Regressor in Numpy from Scratch.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXIV Multilayer Perceptron Regressor in Numpy from Scratch.ipynb -------------------------------------------------------------------------------- /Notebook XXIX Learn the PageRank Algorithm with 1 Simple Example.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXIX Learn the PageRank Algorithm with 1 Simple Example.ipynb -------------------------------------------------------------------------------- /Notebook XXV Multilayer Perceptron Classifier in Numpy from Scratch.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXV Multilayer Perceptron Classifier in Numpy from Scratch.ipynb -------------------------------------------------------------------------------- /Notebook XXVI Pyspark Pipeline.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXVI Pyspark Pipeline.ipynb -------------------------------------------------------------------------------- /Notebook XXVII Custom Pyspark Transformers.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXVII Custom Pyspark Transformers.ipynb -------------------------------------------------------------------------------- /Notebook XXVIII Custom Pyspark Estimators.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXVIII Custom Pyspark Estimators.ipynb -------------------------------------------------------------------------------- /Notebook XXX The Weighted PageRank Algorithm.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXX The Weighted PageRank Algorithm.ipynb -------------------------------------------------------------------------------- /Notebook XXXI Breadth First Search Algorithm.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXXI Breadth First Search Algorithm.ipynb -------------------------------------------------------------------------------- /Notebook XXXII Calculating Max Flow.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXXII Calculating Max Flow.ipynb -------------------------------------------------------------------------------- /Notebook XXXIII Shapley Values for Machine Learning.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXXIII Shapley Values for Machine Learning.ipynb -------------------------------------------------------------------------------- /Notebook XXXIV Area Under the Curve.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXXIV Area Under the Curve.ipynb -------------------------------------------------------------------------------- /Notebook XXXV 3 Methods for Hyperparameter Tuning with Random Forest.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXXV 3 Methods for Hyperparameter Tuning with Random Forest.ipynb -------------------------------------------------------------------------------- /Notebook XXXVI Global Explainability in Machine Learning.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/Notebook XXXVI Global Explainability in Machine Learning.ipynb -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/README.md -------------------------------------------------------------------------------- /[Video] 3 Methods for Hyperparameter Tuning with XGBoost.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/[Video] 3 Methods for Hyperparameter Tuning with XGBoost.ipynb -------------------------------------------------------------------------------- /[Video] Dangling Nodes in PageRank.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/[Video] Dangling Nodes in PageRank.ipynb -------------------------------------------------------------------------------- /[Video] Introduction to Shapley Values.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/[Video] Introduction to Shapley Values.ipynb -------------------------------------------------------------------------------- /[Video] PCA_Biplot.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/[Video] PCA_Biplot.ipynb -------------------------------------------------------------------------------- /[Video] Personalized PageRank.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/[Video] Personalized PageRank.ipynb -------------------------------------------------------------------------------- /[Video] xgboost vs lightgbm vs catboost vs adaboost vs gbm.ipynb: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/[Video] xgboost vs lightgbm vs catboost vs adaboost vs gbm.ipynb -------------------------------------------------------------------------------- /decisiontrees/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/decisiontrees/__init__.py -------------------------------------------------------------------------------- /decisiontrees/abstract/base_tree.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/decisiontrees/abstract/base_tree.py -------------------------------------------------------------------------------- /decisiontrees/treeclassifier.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/decisiontrees/treeclassifier.py -------------------------------------------------------------------------------- /decisiontrees/treeregressor.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/insidelearningmachines/Blog/HEAD/decisiontrees/treeregressor.py --------------------------------------------------------------------------------