This repository curates publicly accessible machine learning engineering courses from top universities like MIT, Stanford, and Berkeley, along with project case studies from industry leaders. It targets individuals seeking to build end-to-end ML engineering skills, offering a structured learning path across foundational computer science, mathematics, AI, machine learning, and specialized areas like NLP and computer vision.

How It Works

The list is organized by topic, covering essential areas from foundational CS and math to advanced ML concepts and deployment. It emphasizes Python for end-to-end ML engineering and includes links to course videos, assignments, textbooks, and reference solutions, facilitating a comprehensive self-study experience.

Quick Start & Requirements

• Install: No installation required; it's a curated list.
• Prerequisites: Access to the internet to view course materials. Python is the preferred language for practical application.
• Resources: Requires time commitment for self-study.
• Links:
  • Official Repo: https://github.com/leehanchung/awesome-full-stack-machine-learning-courses
  • Full Stack Deep Learning: https://fullstackdeeplearning.com/

Highlighted Details

• Comprehensive coverage from foundational CS to specialized ML domains.
• Includes "TL;DR" for a bare-minimum learning path.
• Features project case studies from companies like Google and Facebook.
• Provides links to reference solutions for assignments.

Maintenance & Community

The repository is maintained by Hanchung Lee. Community interaction details (e.g., Discord/Slack) are not specified in the README.

Licensing & Compatibility

• License: CC BY-SA 3.0 for the compilation and reference solutions.
• Compatibility: Course materials are owned by their respective institutions. Commercial use of the compilation is permitted under the CC BY-SA 3.0 license, requiring attribution.

Limitations & Caveats

The list is a compilation of external resources; the quality and availability of linked courses are subject to the originating institutions. Some links may become outdated.