Awesome Python Data Science

An Open Source Machine Learning Framework for Everyone

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

Caffe: a fast open framework for deep learning.

Visualizer for neural network, deep learning and machine learning models

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

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.

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

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

Open standard for machine learning interoperability

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.

Datasets, Transforms and Models specific to Computer Vision

🦉 Data Versioning and ML Experiments

Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

A hyperparameter optimization framework

Image augmentation for machine learning experiments.

NLTK Source

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

A toolkit for making real world machine learning and data analysis applications in C++

A very simple framework for state-of-the-art Natural Language Processing (NLP)

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

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

Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Fast and Accurate ML in 3 Lines of Code

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

A unified framework for machine learning with time series

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

TensorFlow-based neural network library

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

Deep learning library featuring a higher-level API for TensorFlow.

A python library for user-friendly forecasting and anomaly detection on time series.

AutoML library for deep learning

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.

Deep universal probabilistic programming with Python and PyTorch

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀

tensorboard for pytorch (and chainer, mxnet, numpy, ...)

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

An open source python library for automated feature engineering

Efficiently computes derivatives of NumPy code.

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

Fit interpretable models. Explain blackbox machine learning.

A Python scikit for building and analyzing recommender systems

A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

A scikit-learn compatible neural network library that wraps PyTorch

Uplift modeling and causal inference with machine learning algorithms

A system for quickly generating training data with weak supervision