Awesome Python Data Science

An Open Source Machine Learning Framework for Everyone

Visualizer for neural network, deep learning and machine learning models

The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.

Open standard for machine learning interoperability

Low-code framework for building custom LLMs, neural networks, and other AI models

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

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

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

ML powered analytics engine for outlier detection and root cause analysis.

Framework and Library for Distributed Online Machine Learning

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

Cleora AI is a general-purpose open-source model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. Created by Synerise.com team.

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.