GitHub - insidelearningmachines/Blog: This repository is meant to store the code examples used in articles posted on www.insidelearningmachines.com. Each article on the website will have an associated jupyter notebook here with the same name.

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In this repository, you can find the complete python3 code examples used on www.insidelearningmachines.com. Key articles on the aforementioned website will have an associated jupyter notebook located here.

I used anaconda to setup the environment required to develop the code presented here, however you are not limited to this.

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This repository is meant to store the code examples used in articles posted on www.insidelearningmachines.com. Each article on the website will have an associated jupyter notebook here with the same name.

www.insidelearningmachines.com

GitHub - insidelearningmachines/Blog: This repository is meant to store the code examples used in articles posted on www.insidelearningmachines.com. Each article on the website will have an associated jupyter notebook here with the same name.

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Name		Name	Last commit message	Last commit date
Latest commit History 84 Commits
decisiontrees		decisiontrees
Notebook I Linear Regression.ipynb		Notebook I Linear Regression.ipynb
Notebook II Logistic Regression.ipynb		Notebook II Logistic Regression.ipynb
Notebook III Decision Trees.ipynb		Notebook III Decision Trees.ipynb
Notebook IV Bootstrap.ipynb		Notebook IV Bootstrap.ipynb
Notebook IX PCA.ipynb		Notebook IX PCA.ipynb
Notebook V Bagging.ipynb		Notebook V Bagging.ipynb
Notebook VI Random Forest.ipynb		Notebook VI Random Forest.ipynb
Notebook VII Boosting.ipynb		Notebook VII Boosting.ipynb
Notebook VIII Boosting Classification.ipynb		Notebook VIII Boosting Classification.ipynb
Notebook X Adaboost Classification.ipynb		Notebook X Adaboost Classification.ipynb
Notebook XI Adaboost Regression.ipynb		Notebook XI Adaboost Regression.ipynb
Notebook XII Gradient Boost Regression.ipynb		Notebook XII Gradient Boost Regression.ipynb
Notebook XIII KNN.ipynb		Notebook XIII KNN.ipynb
Notebook XIV Pandas Data Pipelines.ipynb		Notebook XIV Pandas Data Pipelines.ipynb
Notebook XIX Perceptron.ipynb		Notebook XIX Perceptron.ipynb
Notebook XV KNN Recommender System.ipynb		Notebook XV KNN Recommender System.ipynb
Notebook XVI Decision Trees with Missing Values.ipynb		Notebook XVI Decision Trees with Missing Values.ipynb
Notebook XVII Decision Trees with Categorical Features.ipynb		Notebook XVII Decision Trees with Categorical Features.ipynb
Notebook XVIII K-Means.ipynb		Notebook XVIII K-Means.ipynb
Notebook XX Batch Gradient Descent.ipynb		Notebook XX Batch Gradient Descent.ipynb
Notebook XXI Stochastic Gradient Descent.ipynb		Notebook XXI Stochastic Gradient Descent.ipynb
Notebook XXII Mini-Batch Gradient Descent.ipynb		Notebook XXII Mini-Batch Gradient Descent.ipynb
Notebook XXIII What is a Sklearn Pipeline?.ipynb		Notebook XXIII What is a Sklearn Pipeline?.ipynb
Notebook XXIV Multilayer Perceptron Regressor in Numpy from Scratch.ipynb		Notebook XXIV Multilayer Perceptron Regressor in Numpy from Scratch.ipynb
Notebook XXIX Learn the PageRank Algorithm with 1 Simple Example.ipynb		Notebook XXIX Learn the PageRank Algorithm with 1 Simple Example.ipynb
Notebook XXV Multilayer Perceptron Classifier in Numpy from Scratch.ipynb		Notebook XXV Multilayer Perceptron Classifier in Numpy from Scratch.ipynb
Notebook XXVI Pyspark Pipeline.ipynb		Notebook XXVI Pyspark Pipeline.ipynb
Notebook XXVII Custom Pyspark Transformers.ipynb		Notebook XXVII Custom Pyspark Transformers.ipynb
Notebook XXVIII Custom Pyspark Estimators.ipynb		Notebook XXVIII Custom Pyspark Estimators.ipynb
Notebook XXX The Weighted PageRank Algorithm.ipynb		Notebook XXX The Weighted PageRank Algorithm.ipynb
Notebook XXXI Breadth First Search Algorithm.ipynb		Notebook XXXI Breadth First Search Algorithm.ipynb
Notebook XXXII Calculating Max Flow.ipynb		Notebook XXXII Calculating Max Flow.ipynb
Notebook XXXIII Shapley Values for Machine Learning.ipynb		Notebook XXXIII Shapley Values for Machine Learning.ipynb
Notebook XXXIV Area Under the Curve.ipynb		Notebook XXXIV Area Under the Curve.ipynb
Notebook XXXV 3 Methods for Hyperparameter Tuning with Random Forest.ipynb		Notebook XXXV 3 Methods for Hyperparameter Tuning with Random Forest.ipynb
Notebook XXXVI Global Explainability in Machine Learning.ipynb		Notebook XXXVI Global Explainability in Machine Learning.ipynb
Notebook XXXVII Advanced Tuning in Keras.ipynb		Notebook XXXVII Advanced Tuning in Keras.ipynb
Notebook XXXVIII 4 techniques for unbalanced data.ipynb		Notebook XXXVIII 4 techniques for unbalanced data.ipynb
README.md		README.md
[Video] 3 Methods for Hyperparameter Tuning with XGBoost.ipynb		[Video] 3 Methods for Hyperparameter Tuning with XGBoost.ipynb
[Video] Cross Validation.ipynb		[Video] Cross Validation.ipynb
[Video] Dangling Nodes in PageRank.ipynb		[Video] Dangling Nodes in PageRank.ipynb
[Video] Introduction to Shapley Values.ipynb		[Video] Introduction to Shapley Values.ipynb
[Video] PCA_Biplot.ipynb		[Video] PCA_Biplot.ipynb
[Video] Personalized PageRank.ipynb		[Video] Personalized PageRank.ipynb
[Video] xgboost vs lightgbm vs catboost vs adaboost vs gbm.ipynb		[Video] xgboost vs lightgbm vs catboost vs adaboost vs gbm.ipynb