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A free learning guide on Agentic AI designed for high school students, available as a PDF on Google Drive.
A structured course built from personal study notes of the book *Linux Basics for Hackers* by OccupyTheWeb, covering core Linux concepts and commands for cybersecurity beginners.
KL Zero is an interactive browser game where players draw a probability distribution to match a target KL divergence value, helping users intuitively understand the concept of KL divergence in machine learning.
A glossary from TechCrunch that defines common AI terms such as AGI, AI agents, API endpoints, and chain of thought, updated regularly as the field evolves.
An interactive visual guide explaining the Constant-Q Transform (CQT), its log-frequency geometry, comparison with FFT, kernel construction, and efficient computation, tailored for music and pitch analysis.
An interactive visual guide that explains how large language models work, from tokenization through attention, transformer blocks, and text generation, built by Roy van Rijn.
An interactive web-based tool that visualizes 24 algorithms step-by-step, covering pathfinding, sorting, recursion, and more, built with React.
A curated video-guided curriculum and comprehensive list of resources for learning ML systems and LLM infrastructure, including papers, courses, and tutorials.
Hugging Face offers a deep reinforcement learning course with practical exercises, now in low-maintenance state but still a useful resource for learning theory and hands-on DRL.
A full educational series on local LLMs, covering inference, tokens, weights, and system-level understanding for beginners and reference.
A comprehensive guide to AI agents, covering the basics, the ReAct loop, task decomposition, context engineering, and the autonomy spectrum, aimed at both beginners and those building production systems.
Sebastian Raschka added a from-scratch implementation of DeepSeek Sparse Attention (DSA) to the LLMs-from-scratch educational repository, including motivation, overview, and a GPT-style reference implementation.
Google DeepMind chip engineer Reiner Pope delivers a comprehensive whiteboard explanation of how chips work, covering logic gates to systolic arrays and the human brain, in a free YouTube video.
This Twitter thread highlights Stanford CS221 lecture 6 on heuristics, explaining how A* search improves agent efficiency by using heuristics to guide decision-making. Key takeaways include building heuristics by relaxing problems, the danger of bad heuristics, and the optimality of A* with the right estimate.
A developer created a free 40-minute breakdown explaining 20 key AI concepts behind models like Claude and ChatGPT, covering tokenization, attention, RAG, agents, and more, aiming to provide practical mental models for builders.
Introduces a Rust macro that suppresses borrow checker errors for educational purposes, warning it is unsafe for production use.
An X thread highlights that Anthropic pays engineers $500K+ to deploy what Percy Liang teaches for free in Stanford CS221 Lecture 3, explaining how watching it changes understanding of Claude's behavior.
A tweet recommends a clear explanation of transformers, urging readers to read it twice.
Stanford provides an explanatory document on Artificial Intelligence & Machine Learning, available via Google Drive.
An archival version of John Regehr's C integers quiz, wrapped in JavaScript for browser compatibility, highlighting tricky undefined behavior and integer issues in C code.