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A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

A python library for decision tree visualization and model interpretation.

Bare bone examples of machine learning in TensorFlow

Feature engineering package with sklearn like functionality

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

? MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained

Leave One Feature Out Importance

EvalML is an AutoML library written in python.