#Data-science
Showing 60 of 3139 repositories tagged #data-science, ranked by stars
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Apache Superset is a Data Visualization and Data Exploration Platform
The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
scikit-learn: machine learning in Python
Deep Learning for humans
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Learn how to develop, deploy and iterate on production-grade ML applications.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Summer 2026 software engineering, data science, AI, quant, product management, and hardware internship postings. Updated daily by Simplify and Pitt CSC.
Streamlit โ 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. ๐ Star to support our work!
10 Weeks, 20 Lessons, Data Science for All!
500 AI Machine learning Deep learning Computer vision NLP Projects with code
๐ซ Industrial-strength Natural Language Processing (NLP) in Python
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Roadmap to becoming an Artificial Intelligence Expert in 2022
๐ Papers & tech blogs by companies sharing their work on data science & machine learning in production.
:memo: An awesome Data Science repository to learn and apply for real world problems.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
๐ธ๏ธ Web apps in pure Python ๐
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
The fastai book, published as Jupyter Notebooks
Data Apps & Dashboards for Python. No JavaScript Required.
๐ A ranked list of awesome machine learning Python libraries. Updated weekly.
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
matplotlib: plotting with Python
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
Best Practices on Recommendation Systems
A reactive notebook for Python โ 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.
AKShare is an elegant and simple financial data interface library for Python, built for human beings! ๅผๆบ่ดข็ปๆฐๆฎๆฅๅฃๅบ
VIP cheatsheets for Stanford's CS 229 Machine Learning
Code for Machine Learning for Trading, 3rd edition โ from data sourcing to live execution.
๐บ Discover the latest machine learning / AI courses on YouTube.
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
Topic Modelling for Humans
An orchestration platform for the development, production, and observation of data assets.
๐ฆ Data Versioning and ML Experiments
Your new Mentor for Data Science E-Learning.
A curated list of awesome big data frameworks, ressources and other awesomeness.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
A curated list of references for MLOps
Statistical data visualization in Python
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. ๐https://aka.ms/RD-Agent-Tech-Report
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Python training for business analysts and traders
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Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
๐ฅHighlighting the top ML papers every week.
The "Python Machine Learning (1st edition)" book code repository and info resource
OpenRefine is a free, open source power tool for working with messy data and improving it
An open-source NLP research library, built on PyTorch.
Low-code framework for building custom LLMs, neural networks, and other AI models
Always know what to expect from your data.
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.
Statsmodels: statistical modeling and econometrics in Python
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.