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.
Simple and Distributed Machine Learning
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
A library for debugging/inspecting machine learning classifiers and explaining their predictions
Microsoft Distributed Machine Learning Toolkit
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
A collection of research papers on decision, classification and regression trees with implementations.
[UNMAINTAINED] Automated machine learning for analytics & production
MLBox is a powerful Automated Machine Learning python library.
Time series forecasting with machine learning models
Scalable Python DS & ML, in an API compatible & lightning fast way.
Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.
A curated list of gradient boosting research papers with implementations.
Scalable machine 🤖 learning for time series forecasting.
An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
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