data-science

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.

Summer 2027 software engineering, data science, AI, quant, product management, and hardware internship postings. Updated daily by Simplify and Pitt CSC.

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!

10 Weeks, 20 Lessons, Data Science for All!

500 AI Machine learning Deep learning Computer vision NLP Projects with code

💫 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.

Roadmap to becoming an Artificial Intelligence Expert in 2022

📚 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.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

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.

🕸️ Web apps in pure Python 🐍

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.

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

Prefect is a workflow orchestration framework for building resilient data pipelines in Python.

matplotlib: plotting with Python

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.