General Resources

Blogs

• https://eugeneyan.com/ (covers a lot of practical issues involved in productising LLM applications, great mix of engineering and data science; both practical and well grounded writing)
  • https://eugeneyan.com/writing/evals/
  • https://eugeneyan.com/writing/llm-patterns/
  • https://eugeneyan.com/writing/llm-evaluators/
• https://applied-llms.org/
• https://lilianweng.github.io/ (posts generally go deeper into the theory and math)
  • https://lilianweng.github.io/posts/2024-07-07-hallucination/
  • https://lilianweng.github.io/posts/2023-10-25-adv-attack-llm/
  • https://lilianweng.github.io/posts/2023-06-23-agent/
• https://newsletter.maartengrootendorst.com/p/a-visual-guide-to-quantization
• https://www.answer.ai/posts/2024-07-25-transformers-as-matchers.html
• https://www.linkedin.com/posts/damienbenveniste_these-days-you-blink-and-there-are-20-new-activity-7178417751282081793-EyiP?utm_source=share&utm_medium=member_desktop (Mixture of Experts Summary)
• https://hamel.dev/
  • https://hamel.dev/blog/posts/llm-judge/
  • https://hamel.dev/blog/posts/evals/#the-types-of-evaluation
  • https://hamel.dev/blog/posts/prompt/
  • https://hamel.dev/blog/posts/evals-faq/?ck_subscriber_id=2765501412&utm_source=convertkit&utm_medium=email&utm_campaign=To What Extent Can You Automate or Outsource Evals? - 18425409
• https://www.latent.space/p/2025-papers

Lectures/Videos/Courses

• https://www.youtube.com/@MachineLearningStreetTalk/videos
• https://parlance-labs.com/education/
• https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/
• https://github.com/rasbt/LLMs-from-scratch
• https://www.youtube.com/watch?v=ZaQYM-YF1rM
• https://rdi.berkeley.edu/llm-agents/f24
• https://web.stanford.edu/class/cs25/index.html#course