The resources on this page are shared to inspire curiosity and support learning. If you know of a valuable resource or have something insightful to share, feel free to reach out.
Open Source
One of the greatest byproducts of the internet is large-scale collaboration on open source projects. I contributed to:
Mathematics & Statistics
- 3Blue1Brown (the series on transformers and neural networks is especially good)
- Visualizing Complex Functions (the segment at 13:04 offers the best visuals of complex functions I’ve found so far)
Machine Learning & AI
- Understanding Deep Learning (the further reading section is especially well curated)
- Hugging Face Daily Papers (daily feed of new model releases and papers)
- Andrej Karpathy (hands-on tutorials built from scratch, no library abstractions)
- Yannic Kilcher (in-depth paper readings)
- Maarten Grootendorst (visual guides to ML concepts)
- NVIDIA NIM APIs (endpoints for many LLMs, several free to use)
- Leaked System Prompts
- UltraScale (Hugging Face’s guide on large scale LLM training)
- Tensor Puzzles (21 exercises to reimplement NumPy/PyTorch functions from scratch, broadcasting only)
- Building AI Agents: From Design Patterns to Production (21 agentic design patterns)
- Stanford CS224R, Deep Reinforcement Learning
- Frontier Model Training Methodologies
Computer Science & Engineering
- Operating System Concepts
- How Linux Works: What Every Superuser Should Know
- System Design Interview (each chapter dissects a well-known system, e.g., Google Drive, Twitter etc.)
- Dive Into Design Patterns
- Simon Oz (introduction to GPU architecture and GPU computing)
- CUDA Tutorial
- Tensor and Fully Sharded Data Parallelism
- Cloudflare Tunnel (exposes a local server to the internet without opening ports on your router)
- PythonAnywhere (free hosting for servers with <500MB RAM)
- WhatsApp Encryption Overview (down to the actual cryptographic primitives used)
Robotics
Finance
- A Random Walk Down Wall Street
- The Elements of Investing (shorter and blunter than the above, if you only read one)
- Educati e Finanziati (personal finance course, Italy-centric)
- Money Guy Show (personal finance course, US-centric)
- How I made $500k with machine learning (one engineer running an HFT strategy alone in 2009-2010)
- Max Dama on HFTs (what it actually takes to succeed in high-frequency trading)
- Quantitative Trading Summary (the whole Headlands blog is worth exploring)
Suggested Readings
Articles, books, blog posts and talks worth checking out.
- Demystifying the American Graduate Admissions Process (by a Stanford admissions committee member)
- Should You Apply for a PhD in AI (2025-26)?
- The unconscious process that leads to creativity: how ‘incubation’ works
- Doing Well in Your Courses (Karpathy on being an undergraduate, something I wish I’d found sooner)
- A Survival Guide to a PhD (same as above, but for a PhD)
- How I Became a Linux Kernel Contributor (step-by-step to getting your first PR merged)
- My Ten Rules for Negotiating a Job Offer
- How to Be Good at Research (on how research is actually learned, since it’s rarely taught directly)
- ML Job Interviews: The Ultimate Guide (inside look at landing a Research Scientist role at a top lab)
- Doing a PhD and Mental Health (on navigating frustration, expectations, and supervisor dynamics)
- You and Your Research (on what makes great research and great researchers)
- How to Approach Research (segment starting at 34:00 on research methodology and mindset)
Misc
Useful tips, solutions, and interesting facts I wish I’d known sooner or simply find worth sharing.
- A visual guide to major AI/ML/Robotics conference templates.
- Converting
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