cheatsheets-ai is an open-source repository that collects essential cheat sheets covering many tools and concepts used in machine learning, deep learning, and data science. The project aims to provide quick-reference materials that help engineers, researchers, and students review key techniques and frameworks without reading extensive documentation. It compiles cheat sheets for widely used libraries and technologies such as TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Matplotlib, and PySpark. These materials summarize common functions, workflows, and best practices in a concise visual format that makes them easy to consult during development or study sessions. The repository functions as a centralized library where users can quickly access reference materials for both machine learning theory and practical programming tools. Many of the cheat sheets are available as downloadable PDFs and images, allowing learners to keep them as quick references while working on projects.
Features
- Collection of cheat sheets for machine learning and deep learning frameworks
- Reference guides for libraries such as TensorFlow, Keras, and NumPy
- Visual summaries of common programming workflows and algorithms
- Downloadable PDF and image cheat sheet formats
- Coverage of data science tools including Pandas, Matplotlib, and PySpark
- Quick-reference materials designed for engineers, researchers, and students