When you remember the library but not the syntax

What it does

This repository is a curated catalog of Jupyter Notebook cheat sheets and reference code for the Python data-science ecosystem. It covers the full stack from data ingestion and SQL through visualization to deep learning, bundling quick lookups for libraries like Pandas, PyTorch, TensorFlow, and Scikit-Learn. The project is maintained by the Chinese AI-education community ShowMeAI and targets practitioners who need fast answers rather than walkthroughs.

The interesting bit

Rather than dumping static PDFs, every cheat sheet is packaged as a runnable Jupyter Notebook, turning reference material into something you can execute, tweak, and copy-paste directly into a pipeline. The breadth is unusually comprehensive for a single community repo, squeezing regular expressions, Spark, OpenCV, and Bokeh into the same collection alongside the usual NumPy and Keras suspects.

Key highlights

• 17 topic-specific folders, including SQL, Bokeh, Spark, and OpenCV alongside standard ML libraries
• Each section ships as a Jupyter Notebook with a visual preview image
• Maintained by ShowMeAI, a Chinese AI-education community
• Covers the full stack: data I/O, visualization, classical ML, deep learning, and computer vision
• Designed for quick problem solving rather than end-to-end tutorials

Verdict

Worth bookmarking if you work across the Python AI stack and prefer executable snippets to browser tabs. Less useful if you need narrative explanations or official English-language documentation.