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Promotion of 'Patterns, Predictions, and Actions: Foundations of Machine Learning' by Moritz Hardt and Benjamin Recht as a free PDF download. The book covers machine learning from fundamentals to societal impact.
Kirk Borne shares a recommendation for a textbook on linear algebra for data science, machine learning, and signal processing, with links to Amazon and praise from academics.
Roman Vershynin's textbook 'High-Dimensional Probability' second edition is available as a free PDF download from the author's website, targeting doctoral students and researchers in data science.
A blog post shares a free PDF of 'All You Wanted to Know about Mathematics but Were Afraid to Ask: Mathematics for Science Students, Volume 2' by Louis Lyons, covering advanced mathematics topics for physics and engineering students.
A 585-page open-access PDF textbook on game theory from arXiv, containing 165 solved exercises.
A free PDF of the Linear Algebra textbook by David Cherney, Tom Denton, and Andrew Walton from UC Davis is shared, emphasizing its importance for AI and data science.
MIT offers the free textbook 'Structure and Interpretation of Computer Programs' (SICP) for learning computer science fundamentals like recursion, abstraction, and language design.
A free PDF of the textbook 'Mathematics for Computer Science' by Eric Lehman, F. Thomson Leighton, and Albert R. Meyer is available via MIT OpenCourseWare, providing essential discrete mathematics foundations for computer science.
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.
A free online textbook covering the fundamentals of wireless communication, including MIMO, space-time coding, OFDM, and CDMA, intended for graduate students and practicing engineers.
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.
Recommending the MIT classic textbook 'Mathematics for Computer Science', suitable for computer science beginners to systematically learn foundational mathematics.
A textbook covering the detailed design of RISC-V microprocessors and system-on-chip, including open-source SystemVerilog code and test cases for single-issue, superscalar, and multicore implementations.
A free online textbook on compiler construction by Prof. Douglas Thain, enabling readers to build a compiler for a C-like language to X86 or ARM assembly, available for download or purchase.
A free open textbook 'Introduction to Theoretical Computer Science' used in Harvard courses is announced, covering foundational theory including computation, algorithms, complexity, and quantum computing.
A free textbook 'Mathematics for Computer Science' is available under CC BY-SA 3.0, covering key topics for computer science students.
A paper titled 'The Hitchhiker's Guide to Agentic AI: From Foundations to Systems' provides comprehensive textbook-like resources on the basics of LLMs and agentic AI.
Harvard has open-sourced a comprehensive two-volume Machine Learning Systems textbook that covers engineering AI systems for real-world constraints, including distributed training, production inference, edge deployment, and governance, with hands-on components like TinyTorch, hardware kits, and interactive tools.
A free online book covering computer science from the bottom up, written by Ian Wienand and available in PDF, EPUB, and source code formats.
Introducing the open-source textbook 'Mathematical Foundations of Reinforcement Learning', which explains reinforcement learning in a simple yet mathematically rigorous manner. It comes with extensive videos and code implementations, suitable for learners with a basic background in probability theory and linear algebra.