Machine Learning Systems

Mike's Notes

I discovered this list of free learning resources by reading Rohit Kumar Tiwari's Substack. The teachers are excellent. This is a compilation of his Substack posts.

• Machine Learning Systems book (Harvard)
• CS336: Language Modelling from Scratch (Stanford)
• CS229: Machine Learning (Stanford)
• CS295: Transformers & LLMs (Stanford)
• 6.S087: Foundation models and generative AI (MIT)
• Learn to Build AI Agents (Microsoft Developer)

Resources

• https://awesomeneuron.substack.com/
• https://github.com/harvard-edge/cs249r_book
• https://mlsysbook.ai/assets/downloads/Machine-Learning-Systems.pdf
• https://stanford-cs336.github.io/spring2025/
• https://www.youtube.com/playlist?list=PLoROMvodv4rOCXd21gf0CF4xr35yINeOy
• https://cs229.stanford.edu/
• https://www.youtube.com/watch?v=9vM4p9NN0Ts
• https://cme295.stanford.edu/syllabus/
• https://www.youtube.com/playlist?list=PLoROMvodv4rOCXd21gf0CF4xr35yINeOy
• https://ocw.mit.edu/courses/6-s087-foundation-models-and-generative-ai-january-iap-2024/
• https://www.youtube.com/playlist?list=PLXV9Vh2jYcjbnv67sXNDJiO8MWLA3ZJKR
• https://www.youtube.com/playlist?list=PLlrxD0HtieHgKcRjd5-8DT9TbwdlDO-OC

References

• Reference

Repository

• Home > Ajabbi Research > Library >
• Home > Handbook > 

Last Updated

2/01/2026

Machine Learning Systems

By: Rohit Kumar Tiwari

Awesome Neuron: 24/12/2025

Simplifying AI for Everyone | Sr. Data Scientist | A Decade of Experience | Creator of AwesomeNeuron | Top 1% @Topmate | Writes to 16K+ @LinkedIn | GenAI, LLMs, Agents.

Harvard University

Machine Learning Systems

A free book by Prof Vijay Janapa Reddi (PDF)

Stanford University

CS336: Language Modelling from Scratch

17 Videos. Language models serve as the cornerstone of modern natural language processing (NLP) applications and open up a new paradigm of having a single general purpose system address a range of downstream tasks. As the field of artificial intelligence (AI), machine learning (ML), and NLP continues to grow, possessing a deep understanding of language models becomes essential for scientists and engineers alike. This course is designed to provide students with a comprehensive understanding of language models by walking them through the entire process of developing their own. Drawing inspiration from operating systems courses that create an entire operating system from scratch, we will lead students through every aspect of language model creation, including data collection and cleansing for pre-training, transformer model construction, model training, and evaluation before deployment.

CS229: Machine Learning

The fastest way I know to really understand AI.

Stanford CS229. Free. 20 lectures.

Course taught by legendary Andrew Ng.

CS295: Transformers & LLMs

These 9 lectures from Stanford are a pure goldmine for anyone wanting to understand LLMs in depth.

MIT

6.S0087: Foundation Models and Generative AI

MIT literally packed 7 hours with everything you need to know about GenAI for FREE.

Microsoft Developer

Learn to Build AI Agents

13 videos. Just 2 hours. Free on YouTube.