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Logical Chess: Move By Move — Every Move Explained: link.amazon/B0c6Z6oXN Perhaps the best Chess book ever for advanced beginners. I remember reading, pondering, and learning from a few pages of an earlier edition of this book each day many years ago on my bus rides to and from work. Format consists of awesome, compelling, logical explanations of every move from dozens of historic games. These brilliant logical explanations are incredibly informative, interesting, and educational. Analytical thinkers will love this book.💛🧡

The Game Theory Method — Concepts, Worked Examples, and Exercises for Strategic Thinkers | Nash Equilibrium, Mixed Strategies, Sequential and Bayesian Games: link.amazon/B0ayPHL47

3 types of Analytics: 1) Know the past with Descriptive. 2) See the future with Predictive. 3) Optimize the future with Prescriptive. The aim of Predictive Analytics is to predict the future. The aim of Prescriptive Analytics is to change (optimize) the future. But wait! Here are 3 more variants — Sentinel, Precursor, and Cognitive (“funky”) Analytics: rocketdatascience.org/?p=197…

Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques — A Data Science Guide: amzn.to/2rIXpyQ

Building Reliable AI Systems, Applications, and Agents that you can trust: link.amazon/B0bp9BbLL

AI Fundamentals: Understand AI, evaluate its capabilities, and apply it responsibly — Builder’s Guide to Artificial Intelligence, Machine Learning, ... LLMs, and Responsible AI — No Coding Required Get it at link.amazon/B0hX1wl2W

Replacement — The AI Revolution Isn’t Coming for Your Job. It Already Took It ➡️link.amazon/B03mV9oJG ⬅️

Strategic Foresight in the Era of Human-Centric AI: link.amazon/B06u1DX63

The book "Info We Trust" brings poetry to the craft of designing with numbers and celebrates Data Storytelling — "data visualization needs a book like this." ➡️ amzn.to/2Wvikqa ⬅️

“Just Six Numbers to Represent the Deep Forces that Shape the Universe”, by Martin Rees Get the book at amzn.to/3WlpY3M ————— #Astrophysics #Physics #Cosmology #Astronomy

Topological Data Analysis with Applications: amzn.to/3Sn7QrN What kind of Applications? Here are some: ◉ Modeling data for geometric objects ◉ Modeling complex graphs & networks ◉ Modeling high-dimensional datasets 🔴The book also examines a number of case studies drawn from monitoring the progression of infectious diseases to the study of motion capture data.🔴

Volume 1 - Notes and Problems in Number Theory: link.amazon/B0hQGIbgW Volume 2 - Notes and Problems in Number Theory: link.amazon/B0aQiD5NG #Mathematics

Math Study Guide — 750 Realistic Mathematics Questions With Detailed Explanation Covering Number Systems, Functions, Probability, Calculus and Geometry: amzn.to/4wcNdMC

“Exploring the Beauty of Fascinating Numbers” Available at amzn.to/4qPUFuo by @NumbersByShyam

Investing for Programmers — Understanding markets through data and code: amzn.to/46NkpRc

Explore math book best-sellers, whether to build your own mathematics skillset or to help others build their math confidence. Start exploring here: amzn.to/4jRbZO2 Become Math-ish! — thnx @joboaler 🏆 Math-ish = Finding Meaning in Mathematics: amzn.to/4cLqGNn

Model to Meaning — How to interpret Statistical Models with R and Python: amzn.to/46jaB0o — Concrete workflows, task-specific software, and detailed case studies, presented using real-world data and code examples.

Ontology Pipeline — Framework for Knowledge Engineering and Building Knowledge Infrastructures: link.amazon/B06B2xJy5 Amazon description: “One of the biggest shifts happening in our industry is that enterprise data management is expanding into enterprise knowledge management. AI is accelerating that transition because it depends on more than well-managed data. It depends upon context, shared meaning, trusted relationships, and the ability to organize the vast stores of unstructured knowledge that exist across every large enterprise. As AI becomes the primary interface to enterprise information, knowledge management will become the foundation that unlocks trustworthy AI at scale.”

“Seeing with Fresh Eyes — Meaning, Space, Data, Truth”, by the legendary Edward Tufte Here ➡️ link.amazon/B0edoTrLW