data-science
There are 55843 repositories under data-science topic.
microsoft/ML-For-Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
apache/superset
Apache Superset is a Data Visualization and Data Exploration Platform
keras-team/keras
Deep Learning for humans
scikit-learn/scikit-learn
scikit-learn: machine learning in Python
pandas-dev/pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
GokuMohandas/Made-With-ML
Learn how to design, develop, deploy and iterate on production-grade ML applications.
apache/airflow
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
streamlit/streamlit
Streamlit — A faster way to build and share data apps.
gradio-app/gradio
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
ray-project/ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
explosion/spaCy
💫 Industrial-strength Natural Language Processing (NLP) in Python
microsoft/Data-Science-For-Beginners
10 Weeks, 20 Lessons, Data Science for All!
AMAI-GmbH/AI-Expert-Roadmap
Roadmap to becoming an Artificial Intelligence Expert in 2022
Lightning-AI/pytorch-lightning
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
donnemartin/data-science-ipython-notebooks
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.
eriklindernoren/ML-From-Scratch
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.
eugeneyan/applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
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 ;)
academic/awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
500 AI Machine learning Deep learning Computer vision NLP Projects with code
d2l-ai/d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
plotly/dash
Data Apps & Dashboards for Python. No JavaScript Required.
fastai/fastbook
The fastai book, published as Jupyter Notebooks
sinaptik-ai/pandas-ai
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
lukasmasuch/best-of-ml-python
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
matplotlib/matplotlib
matplotlib: plotting with Python
recommenders-team/recommenders
Best Practices on Recommendation Systems
PrefectHQ/prefect
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
afshinea/stanford-cs-229-machine-learning
VIP cheatsheets for Stanford's CS 229 Machine Learning
dair-ai/ML-YouTube-Courses
📺 Discover the latest machine learning / AI courses on YouTube.
ipython/ipython
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
piskvorky/gensim
Topic Modelling for Humans
bharathgs/Awesome-pytorch-list
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
marimo-team/marimo
Transform data, train models, and run SQL with marimo — feels like a next-gen reactive notebook, stored as Git-friendly reproducible Python. Deploy as scripts, pipelines, endpoints, and apps. All from an AI-native editor (or your own).
stefan-jansen/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
iterative/dvc
🦉 Data Versioning and ML Experiments