Awesome Python

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

Open Data Platform for analysts, quants and AI agents.

Open Data Platform for analysts, quants and AI agents.

scikit-learn: machine learning in Python

Deep Learning for humans

Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

Streamlit — A faster way to build and share data apps.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

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

💫 Industrial-strength Natural Language Processing (NLP) in Python

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

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

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

A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.

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.

Topic Modelling for Humans

A hyperparameter optimization framework

NLTK Source

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.

🐍 Geometric Computer Vision Library for Spatial AI

A unified framework for machine learning with time series

Bindu: The identity, communication, and payments layer for AI agents.

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.

Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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

A Python scikit for building and analyzing recommender systems

Lightning ⚡️ fast forecasting with statistical and econometric models.

Fast Python Collaborative Filtering for Implicit Feedback Datasets

PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.

Feature engineering and selection open-source Python library compatible with sklearn.

We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.