The-Algorithmic-Approach-to-Winning-Guess-Who

A game theoretic approach to explain the output of any machine learning model.

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.

A highly extensible Markdown editor. Version control, AI Copilot, mind map, documents encryption, code snippet running, integrated terminal, chart embedding, HTML applets, Reveal.js, plug-in, and macro replacement.

Natural Gradient Boosting for Probabilistic Prediction

小书匠是一款本地优先，去中心化，分布式，支持选择性同步的全平台覆盖知识管理笔记软件。

A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4.

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

Tuning hyperparams fast with Hyperband