Search awesome repositories

Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.

Postgres with GPUs for ML/AI apps.

Statistical Machine Intelligence & Learning Engine

🍊 :bar_chart: :bulb: Orange: Interactive data analysis

mlpack: a fast, header-only C++ machine learning library

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

Powerful modern math library for PHP: Features descriptive statistics and regressions; Continuous and discrete probability distributions; Linear algebra with matrices and vectors, Numerical analysis; special mathematical functions; Algebra

A Julia machine learning framework

Rust library for quantitative finance.

Python AutoML for Trading Systems and Sports Betting

ThunderSVM: A Fast SVM Library on GPUs and CPUs

MLBox is a powerful Automated Machine Learning python library.

A curated list of all machine learning algorithms and deep learning algorithms grouped by category.

A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python

recheck for web apps – change comparison tool with local Golden Masters, Git-like ignore syntax and "Unbreakable Selenium" tests.

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.