This repository provides a curated roadmap and free resources for beginners looking to learn Machine Learning and Artificial Intelligence. It aims to guide individuals through foundational concepts, essential tools, and practical experience, targeting aspiring AI/ML engineers, data scientists, and software engineers.

How It Works

The resource is structured as a comprehensive learning path, starting with core AI/ML concepts and building blocks like linear algebra and Python libraries. It then progresses to fundamental ML algorithms, practical project experience, and specialization in areas like NLP and Computer Vision. The roadmap also includes guidance on MLOps, job interview preparation, and links to relevant courses, certifications, books, tools, research blogs, and communities.

Quick Start & Requirements

• No installation required; it's a curated list of external resources.
• Prerequisites: Basic programming knowledge (Python recommended), foundational math (linear algebra, calculus, probability, statistics).
• Links to official quick-start: Google Machine Learning Crash Course, Andrew Ng's Machine Learning Course, Fast.ai.

Highlighted Details

• Covers a wide range of AI/ML roles from engineer to research scientist.
• Includes a "Problems" section with categorized coding challenges from easy to hard.
• Features links to key research papers like "Attention Is All You Need" and "BERT".
• Curates resources from top institutions like Stanford and platforms like Coursera and edX.

Maintenance & Community

• Maintained by Arman Khondker.
• Links to communities: r/LearnMachineLearning, Chip Huyen's MLOps Discord, Hugging Face Discord.
• Newsletter subscription available for a free AI/ML roadmap.

Licensing & Compatibility

• No explicit license mentioned for the curated list itself.
• Resources linked are from various sources with their own licenses; users must adhere to them. Compatibility for commercial use depends on the licenses of the linked external resources.

Limitations & Caveats

The repository is a curated list and does not host any code or provide direct learning environments. The quality and availability of linked external resources are subject to change by their respective owners.