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 ;)
🧠 Laws, Theories, Principles and Patterns for developers and technologists.
- principles
- laws
- coding
- computerscience
The Open Source Data Science Masters
The fastai book, published as Jupyter Notebooks
Data Apps & Dashboards for Python. No JavaScript Required.
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
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.
Video discussing this curriculum:
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.
TranslatedAKShare is an elegant and simple financial data interface library for Python, built for human beings! Open-source financial data interface library
Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.
📊 Path to a free self-taught education in Data Science!
Best Practices on Recommendation Systems
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
🎓 Um caminho para a educação autodidata em Ciência da Computação!
DevOps Roadmap for 2026. with learning resources
VIP cheatsheets for Stanford's CS 229 Machine Learning
Turns Data and AI algorithms into production-ready web applications in no time.
💿 Free software that works great, and also happens to be open-source Python.
Translated👶🏻 Encyclopedia of major knowledge & technical interviews for junior developers 📖
📺 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.