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Awesome List
Probably the best curated list of data science software in Python.
GitHub stars and default-branch commits for krzjoa/awesome-python-data-science.
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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!
Extremely fast Query Engine for DataFrames, written in Rust
A toolkit for developing and comparing reinforcement learning algorithms.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Caffe: a fast open framework for deep learning.
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.
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)
Graph Neural Network Library for PyTorch
Open standard for machine learning interoperability
Interactive Data Visualization in the browser, from Python
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Datasets, Transforms and Models specific to Computer Vision
Network Analysis in Python
🎨 Python Echarts Plotting Library
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Image augmentation for machine learning experiments.
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
NLTK Source
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)
Python package built to ease deep learning on graph, on top of existing DL frameworks.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
Lime: Explaining the predictions of any machine learning classifier
NumPy & SciPy for GPU
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.
Always know what to expect from your data.
Statsmodels: statistical modeling and econometrics in Python
LAVIS - A One-stop Library for Language-Vision Intelligence
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Fast and Accurate ML in 3 Lines of Code
Modin: Scale your Pandas workflows by changing a single line of code
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
TensorFlow-based neural network library
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
A unified framework for machine learning with time series
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
Bayesian Modeling and Probabilistic Programming in Python
Deep learning library featuring a higher-level API for TensorFlow.
AutoML library for deep learning
Automatic extraction of relevant features from time series:
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.