This repository offers a curated collection of Stanford-developed cheatsheets covering fundamental topics in Artificial Intelligence, Machine Learning, and Deep Learning. It serves as a quick-reference guide for students, developers, and researchers to recall key concepts and formulas.

How It Works

The collection is organized by topic, with each cheatsheet providing concise explanations, diagrams, and essential equations. This approach facilitates rapid review and understanding of complex AI/ML subjects.

Quick Start & Requirements

• Primary install / run command: git clone https://github.com/analyticalrohit/AI-ML-Cheatsheets.git
• Prerequisites: None beyond standard Git.

Highlighted Details

• Comprehensive coverage of AI, Transformers/LLMs, Deep Learning, Machine Learning, Probabilities, Statistics, Algebra, and Calculus.
• Organized folder structure for easy navigation.
• Includes concise explanations, diagrams, and essential equations.

Maintenance & Community

The repository encourages community contributions via pull requests. A newsletter is available for AI/ML enthusiasts.

Licensing & Compatibility

The repository does not explicitly state a license. This may pose compatibility issues for commercial or closed-source use.

Limitations & Caveats

The absence of a specified license requires clarification before any form of integration or redistribution.