Note 1
Further Resources

Throughout learning, I was blessed with countless resources dedicated for machine learning. Therefore, I decided to list recommended readings and other resources I used when studying and writing the notes. A huge shout out to creators for their contributions in machine learning community!

Papers

• All Time Favorites

  • Attention Is All You Need
  • A Mathematical Framework for Transformer Circuits

• LLMs

  • Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
  • Chain-of-Thought Reasoning Without Prompting
  • Language Models are Few-Shot Learners
  • Scaling Laws for Neural Language Models
  • A Neural Probabilistic Language Model
  • Large Language Models: A Survey

• Diffusion Models

  • Hierarchical Text-Conditional Image Generation with CLIP Latents
  • Score-Based Generative Modeling through Stochastic Differential Equations
  • Denoising Diffusion Probabilistic Models
  • Learning Transferable Visual Models From Natural Language Supervision

Websites

• Articles and Blogs

  • Colah’s Blog (Christopher Olah)
  • When AI builds itself (Anthropic)
  • Deep Double Descent (OpenAI)
  • Visualizing K-Means Clustering (Naftali Harris)
  • Jason Osajima (Jason Osajima)
  • ML Foundations: Understanding the Math Behind Backpropagation (Jordan Coblin)

• Miscellaneous

  • MLU-EXPLAIN (Machine Learning University)
  • FrontierMath
  • Machine Learning Mastery
  • xKiwiLabs
  • Distill
  • PyTorch Tutorial

• GitHub

  • ML-From-Scratch (Erik Linder-Norén)

Books and Notes

• Books

  • Goodfellow’s Book
  • Dive into Deep Learning
  • Neural Networks and Deep Learning (Michael Nielsen)
  • Mathematics for Machine Learning
  • Deep Learning with PyTorch
  • Foundations of Computer Vision (Antonio Torralba, Phillip Isola, William Freeman)

• Notes

  • CS229 (Stanford University)
  • Sparse Autoencoder (Andrew Ng)

Courses and Videos

• Courses

  • Practical Deep Learning
  • CME 295 (Stanford University)

• Videos

  • Neural Networks (3Blue1Brown)
  • Neural Networks: Zero to Hero (Andrej Karpathy)

Tools and Datasets

• Tools

  • Weights & Biases
  • OpenRouter
• Datasets

• Platforms

  • Cirleback
  • Fireflies