resources
“Academic weapon” or whatever
2026 Goals
must:
- Karpathy zero to hero
- LLM Architectures: implement all; hand-written notes; git repo and a blog to support.
- Claude Course: how to get great at claude
- Fine Tuning, RAG, Agents, LLMOps google tabs
- Read Hands on LLMs by Jay
- Read Building LLMs from scratch by Sebastian
- [Vizuara DL book]
- HuggingFaces LLM Course
- Read CUDA for DL by Elliot
- Read GenAI Design book
- Read Pre-training, Post-training, RL handbooks by Elliot
- ML Interviews Book
- ML Systems Book along with ML System Design Stanford
- System Design: notes on all, (ML, GenAI, SDE System Design)
- Research papers to read
- State of RL
- Frontier Labs Course
- System Design SDE
- [GKCS Course LLD, HLD]
- FastAPI playlist
- ML Playlist
- Stanford Language Modeling
- UCB Reinforcement Learning
- More LLMOps
- Backend needed for ML Vizuara
blogs
- Modern LLM Architectures
- Inference Engineering (IE book, Physics of LLMs, Google Tabs)
- Pre-training, Post-training, RL in depth
- ML System Design (based on bbg, genaidesign book)
- Karpathy videos blog
- Programming pearls blog
- CUDA blog (post book and elliot video)
- What I learnt from LLM from scratch + Hands on LLMs
- What i learnt from AI Engineering book
- Actually learning LLMs blog
- Learnings from DDIA + SysDesign gkcs course
- Learnings from OS 3 easy pieces + writing your own OS
- VIT vs CNN for images
- Hutter Prize (AI is just compression) TinyLLMZip project
- Learnings from GenAI handbook
- Agentic AI playbook course review
- Learning a new language (scala)
- Backend for ML
projects
- triton flash attention
- autoresearch for vision?
- llmcouncil
- stable diffusion paper
- multimodal vision project
- shelfml + fastapi
- train smol model to write sql
- ai chatbot
- shazam
video to watch + books/website to read
- from tcp to http
- ProbStats
- Computer Vision blogs to write:
- tcpip for programmers
- git video (primegan)
- multi-threading interview questions
- DDIA
- neural networks are decision trees
- docker bare metals, kubernetes
- Train smol model to write SQL project
- alice adventures in differentiable wonderland
- accidental cto
- functional programming in scala
- annotated turing
- inside nvidia gpu
- gpu cornell
- code by charles
- statquest guide to ml
- ml deployment
- what every programmer should know about memory
- journey to the stack
- singularity
- prime intellect