Open Source

I believe one of the greatest byproducts of the internet is large-scale collaboration. People around the world manage to work together to advance open-source projects and build amazing projects.

I co-founded the Bocconi Open Source Society (BOSS) to promote open source at my university, and I contribute to projects whenever I can. Here are some I’ve worked on:

• Understanding Deep Learning textbook by Simon J.D. Prince (The MIT Press, 2023).
• TileDB-Vector-Search, a library for efficient out-of-core vector search.
• Conda package manager.

Check out my collection of code snippets to improve the quality-of-life during your everyday tasks.

Resources by topic

Resources I have found most valuable for learning, exploring, or reviewing different topics.

Mathematics & Statistics

• 3Blue1Brown (the series on transformers and neural networks is especially good)

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)

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)

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, and blog posts worth reading.

• 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
• WhatsApp Encryption Overview (down to the actual cryptographic primitives used)
• 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 patch merged)
• My Ten Rules for Negotiating a Job Offer
• Building AI Agents: From Design Patterns to Production (21 agentic design patterns)
• 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)

Misc

Useful tips, solutions, and interesting facts I wish I’d known sooner or simply find worth sharing.

• Converting .epub to .mobi and then back to .epub can resolve ERROR 999 Internal Problem on Amazon Kindle. See the reference here.
• \(r = 1-\sin(\theta)\) is a heart curve in polar coordinates.

Map My Visitors