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<div align="center"> <a href="https://krzjoa.github.io/awesome-python-data-science/"><img width="250" height="250" src="img/py-datascience.png" alt="pyds"></a> <br> <br> <br> </div> <h1 align="center"> Awesome Python Data Science </h1> <div align="center"><a href="https://github.com/sindresorhus/awesome"> <img src="https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg" alt="Awesome" border="0"> </a> </div> </br>

Probably the best curated list of data science software in Python

Contents

Machine Learning

General Purpose Machine Learning

Gradient Boosting

Ensemble Methods

Imbalanced Datasets

Random Forests

Kernel Methods

Deep Learning

PyTorch

TensorFlow

MXNet

JAX

Others

Automated Machine Learning

Natural Language Processing

Computer Audition

Computer Vision

Time Series

Reinforcement Learning

Graph Machine Learning

Learning-to-Rank & Recommender Systems

Probabilistic Graphical Models

Probabilistic Methods

Model Explanation

Genetic Programming

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Optimization

Feature Engineering

General

Feature Selection

Visualization

General Purposes

Interactive plots

Map

Automatic Plotting

NLP

Deployment

Statistics

Data Manipulation

Data Frames

Pipelines

Data-centric AI

Synthetic Data

Distributed Computing

Experimentation

Data Validation

Evaluation

Computations

Web Scraping

Spatial Analysis

Quantum Computing

Conversion

Contributing

Contributions are welcome! :sunglasses: </br> Read the <a href=https://github.com/krzjoa/awesome-python-datascience/blob/master/CONTRIBUTING.md>contribution guideline</a>.

License

This work is licensed under the Creative Commons Attribution 4.0 International License - CC BY 4.0