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《Start Doing Graph Theory》是一本关于用图论解谜、证明定理的入门教材，采用 Creative Commons 许可免费在线阅读或下载 PDF，现公开发布。
Programming Language Foundations in Agda (PLFA) 是一本使用证明助手 Agda 讲解编程语言理论的开源教材，涵盖逻辑基础、操作语义与指称语义，并列出了多门采用该书授课的高校课程。
Kirk Borne 分享并推荐了教材《Bayes Rules!: An Introduction to Applied Bayesian Modeling》，该书由 Alicia A. Johnson、Miles Q. Ott 和 Mine Dogucu 编写，涵盖共轭先验、MCMC、回归与层级模型，并配有 bayesrule R 包。
一篇介绍莱顿大学发布在 Arxiv 上的472页 AI 教科书《Agentic Large Language Models》的推文，涵盖大模型工作原理、Agent 原则、语言建模基础及 LLM 训练流程等内容。
This is an open-source textbook published by Harvard University, aiming to establish machine learning systems engineering as a quantitative engineering discipline, similar to computer architecture. The book covers ML system design principles from single nodes to ten-thousand-card clusters and emphasizes engineering rather than just model-centric approaches.
MIT professor Gilbert Strang releases a new textbook 'Linear Algebra and Learning from Data' that bridges linear algebra with AI, receiving high ratings and adoption at top institutions.
A free 490-page textbook on causal inference by Peng Ding, covering topics from correlation to longitudinal data with accompanying R code and datasets.
Explorations in Monte Carlo Methods is a hands-on textbook that teaches Monte Carlo methods through realistic problems and programming exercises, suitable for students in engineering, sciences, and mathematics.
The article announces the free availability of the textbook 'Deep Learning on Graphs' by Yao Ma and Jiliang Tang, covering Graph Neural Networks and deep learning on graph-structured data.
This tweet announces the second edition of 'Introduction to Modern Statistics,' an open-source textbook available for free online or at a name-your-own-price PDF.
The fourth edition of Sheldon Axler's 'Linear Algebra Done Right' textbook is now available for free as Open Access in multiple languages, featuring new exercises and improvements, with print versions also available.
Tweet promoting the third edition of the statistics textbook 'Designing Experiments and Analyzing Data: A Model Comparison Perspective' by Maxwell, Delaney, and Kelley, highlighting its pedagogical features and the authors' academic credentials.
A tweet recommending Jeff Erickson's free online algorithms textbook, highlighting its great illustrations and overall quality.
A free open-access textbook on game theory, with 585 pages and 165 solved exercises, is promoted as a resource for economics, AI, computer science, and more.
An introduction to data analysis for social science using R, praised as a practical and accessible textbook for beginners.
A free 674-page PDF of the textbook 'Introduction to Machine Learning' by Laurent Younes is available, covering mathematical foundations and algorithms for machine learning.
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.