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2.2 Machine Epsilon, Rounding, ULPs
A comprehensive, intuitive guide to machine epsilon, rounding behavior, and ULPs in floating-point arithmetic. Learn how precision limits shape numerical accuracy, how rounding errors arise, and why these concepts matter for AI, ML, and scientific computing.
2025-09-09
2.1 Floating-Point Numbers (IEEE 754)
A detailed, intuitive guide to floating-point numbers and the IEEE 754 standard. Learn how computers represent real numbers, why precision is limited, and how rounding, overflow, subnormals, and special values affect numerical algorithms in AI, ML, and scientific computing.
2025-09-08
Chapter 2 — The Computational Model
An introduction to the computational model behind numerical linear algebra. Explains why mathematical algorithms fail inside real computers, how floating-point arithmetic shapes computation, and why understanding precision, rounding, overflow, and memory layout is essential for AI, ML, and scientific computing.
2025-09-07
1.1 What Breaks Real AI Systems
Many AI failures come from numerical instability, not algorithms. This guide explains what actually breaks AI systems and why numerical linear algebra matters.
2025-09-03
Hello World Bot|Mastering Microsoft Teams Bots 2.2
Build your first Microsoft Teams bot with a simple Hello World response. This hands-on section walks you through using the Bot Framework SDK, setting up a local project with Node.js or .NET, using Ngrok to expose your endpoint, and testing your bot directly in Teams.
2025-04-06
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