Tag
Yoshua Bengio's 'Deep Learning' textbook, co-authored with Ian Goodfellow and Aaron Courville, is available for free online at deeplearningbook.org, offering comprehensive coverage of neural networks and related math.
MIT has released the full 900-page discrete mathematics textbook 'Mathematics for Computer Science' for free online, covering proofs, graph theory, state machines, counting, recurrences, and probability as they apply to computer science.
MIT CSAIL shares a free guide answering key reinforcement learning questions.
A former COO of Citadel Securities is offering free insights on where to find profitable opportunities in AI.
A developer published his ML interview prep guide on GitHub for free, based on real questions he received from Google, LinkedIn, Snap, Coupang, and StitchFix, covering study plans, coding, stats, system design, and more; the repo now has 12.4k stars.
A free online book covering computer science from the bottom up, written by Ian Wienand and available in PDF, EPUB, and source code formats.
A 16-hour free YouTube playlist created by @0x0SojalSec teaches how to build a DeepSeek model from scratch, covering papers, theory, and code implementation including attention mechanisms, mixture of experts, and positional encodings.
Recommends a free AI course from Stanford University. It takes just 1.5 hours to break down how Claude and ChatGPT work, helping you deeply understand AI's underlying logic to get more out of them.
Announces the free availability of the 'Competitive Programmer’s Handbook', covering 30 important DSA topics for tech interview preparation.
An interactive, 3D, step-by-step visualizer that shows a token moving through every transformer layer, from embedding to output, for free.
A tweet promoting a 38-page PDF guide on building autonomous LLM agents, offering a free resource for learning about agentic AI systems.
A comprehensive free guide explaining LLMs from first principles, covering tokens, transformers, attention, fine-tuning, and local deployment.
A comprehensive free online guide covering hardware and software for running LLMs locally is now available, detailing setups from laptops to clusters.
A tweet promoting a free deep learning resource with 68 interactive Python notebooks covering topics from basics to advanced techniques like GANs and diffusion models, ideal for self-learners.
Promotion of a free resource on mathematical and statistical methods for data science and machine learning, with instructions to engage for access.
Andrej Karpathy shares his straightforward approach to working with AI, emphasizing plain language over complex prompt engineering, and predicts that by 2026 engineers who dismiss LLMs will lose to juniors who use them effectively.
A senior Google engineer released a free 421-page document covering agentic design patterns for AI systems, with code-backed chapters on prompt chaining, multi-agent coordination, guardrails, and reasoning.
A free downloadable reference card covering the process of building and deploying a website using AI tools, written from first principles.
Google has released a free masterclass on GPUs, covering GPU architecture and deep learning acceleration.
Google engineer publicly released the 421-page Agentic Design Patterns document for free, recommending key chapters for independent developers including MCP protocol, guardrails evaluation, and multi-agent patterns.