Download 674-page PDF >> Introduction to Machine Learning (textbook on foundations, algorithms, and techniques): arxiv.org/abs/2409.02668 ———— #ML #AI #Mathematics #DataScience
→ View original post on X — @kirkdborne, 2026-04-06 05:50 UTC
RESEARCH
-
AI Predicts Japan Cherry Blossoms Bloom Date
By
–
When Will Japan’s Cherry Blossoms Bloom? #AI Can Help Answer That by @HernandezJavier @hudidi1 @nytimes Learn more: bit.ly/3NTsXQi #MachineLearning #ArtificialIntelligence #ML #MI
→ View original post on X — @ronald_vanloon, 2026-04-06 05:50 UTC
-
Game Theory Book: Strategies, Nash Equilibria, and Behavioral Economics
By
–
Fascinating reading on Game Theory: amzn.to/2T70A1y 💥🏆 "A Nontechnical Intro to the Analysis of Strategy" (3rd Ed.), covers N-person strategies, Nash Equilibria, auctions, bargaining, dominant strategies, Gamification, Behavioral Economics, Experimental Economics, etc.
→ View original post on X — @kirkdborne, 2026-04-06 05:44 UTC
-
Deep Reinforcement Learning Hands-On Guide Third Edition Released
By
–
Deep Reinforcement Learning Hands-On — Practical easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF: amzn.to/3MV9o60 [3rd Ed.] —— #AI #MachineLearning #ML #DataScience —— 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼: 🟢Learn with concise explanations, modern libraries, and diverse applications from games to stock trading and web navigation 🔵Speed up RL models using algorithmic and engineering approaches 🟠Learn about human feedback (RLHF), MuZero, and transformers
→ View original post on X — @kirkdborne, 2026-04-06 05:43 UTC
-
Graph Machine Learning 2nd Edition: PyTorch Geometric and DGL Techniques
By
–
Graph Machine Learning — Latest advancements in Graph Data to build robust Machine Learning algorithms (2nd Edition) — at amzn.to/45Y3LyI v/ @PacktDataML 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼: 🟠Master new graph ML techniques through updated examples using PyTorch Geometric and Deep Graph Library (DGL) 🔵Explore GML frameworks and their main characteristics 🟠Leverage LLMs for machine learning on graphs and learn about temporal learning 🔵Purchase of the print or Kindle book includes a free PDF eBook
→ View original post on X — @kirkdborne, 2026-04-06 05:34 UTC
-
Machine Learning Architecture Handbook: Practical MLOps AI Strategies
By
–
Machine Learning Solutions Architect Handbook — Practical Strategies and Best Practices in the ML Lifecycle, System Design, MLOps, and Generative AI: amzn.to/4bx8t6b v/ @PacktDataML [Translated from EN to English]
→ View original post on X — @kirkdborne, 2026-04-06 05:22 UTC
-
IMMACULATE: Auditing LLM Providers with Verifiable Computation
By
–
Can you really trust your black-box LLM provider with correct inference and honest billing? Researchers from NUS, NTU, and UC Berkeley introduce IMMACULATE. This practical auditing framework uses verifiable computation to randomly check a small fraction of LLM requests. It detects economically motivated cheats like model substitution, quality degradation, and token overbilling without needing trusted hardware or internal model access. IMMACULATE reliably distinguishes honest vs. malicious LLM execution in dense and MoE models, adding less than 1% throughput overhead. IMMACULATE: A Practical LLM Auditing Framework via Verifiable Computation Paper: arxiv.org/pdf/2602.22700 Code: github.com/guo-yanpei/Immacu… Our report: mp.weixin.qq.com/s/WR9nXudXT… 📬 #PapersAccepted by Jiqizhixin
→ View original post on X — @jiqizhixin, 2026-04-06 05:13 UTC
-
3D Deep Learning Computer Vision Models with PyTorch3D
By
–
3D Deep Learning with Python — Design and develop Computer Vision models with 3D data using PyTorch3D: http://
amzn.to/491yDwh v/ @PacktDataML ————
#AI #MachineLearning #ML #DataScience #DataScientist #PyTorch -
Reinforcement Learning Foundational Textbook Second Edition Released
By
–
Reinforcement Learning foundational book (2nd edition of this classic mathematical textbook): http://
amzn.to/3UtbeAa
—————
#DataScience #AI #MachineLearning #ML #Mathematics #Gamification -
Time Series Analysis with Python Cookbook Second Edition
By
–
New release from @PacktDataML at http://
amzn.to/4sjCbni "Time Series Analysis with Python Cookbook: Practical recipes for the complete time series workflow, from modern data engineering to advanced forecasting and anomaly detection" [2nd Edition; 812 pages]