{R}R Dev Notes
Found total of 120 articles.
3.4 Exact Algorithms vs Implemented Algorithms
Learn why textbook algorithms differ from the versions that actually run on computers. This chapter explains rounding, floating-point errors, instability, algorithmic reformulation, and why mathematically equivalent methods behave differently in AI, ML, and scientific computing.
2025-09-16
3.3 Conditioning of Problems vs Stability of Algorithms
Learn the critical difference between problem conditioning and algorithmic stability in numerical computing. Understand why some systems fail even with correct code, and how sensitivity, condition numbers, and numerical stability determine the reliability of AI, ML, and scientific algorithms.
2025-09-15
3.1 Norms and Why They Matter
A deep yet accessible exploration of vector and matrix norms, why they matter in numerical computation, and how they influence stability, conditioning, error growth, and algorithm design. Essential reading for AI, ML, and scientific computing engineers.
2025-09-13
Chapter 3 — Computation & Mathematical Systems
A clear, insightful introduction to numerical computation—covering norms, error measurement, conditioning vs stability, and the gap between mathematical algorithms and real implementations. Essential reading for anyone building AI, optimization, or scientific computing systems.
2025-09-12
2.4 Vector and Matrix Storage in Memory
A clear, practical guide to how vectors and matrices are stored in computer memory. Learn row-major vs column-major layout, strides, contiguity, tiling, cache behavior, and why memory layout affects both speed and numerical stability in real systems.
2025-09-11
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
1.4 A Brief Tour of Real-World Failures
A clear, accessible tour of real-world numerical failures in AI, ML, optimization, and simulation—showing how mathematically correct algorithms break inside real computers, and preparing the reader for Chapter 2 on floating-point reality.
2025-09-06
1.3 Computation & Mathematical Systems
A clear explanation of how mathematical systems behave differently inside real computers. Learn why stability, conditioning, precision limits, and computational constraints matter for AI, ML, and numerical software.
2025-09-05
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
1.0 Why Numerical Linear Algebra Matters
A deep, practical introduction to why numerical linear algebra matters in real AI, ML, and optimization systems. Learn how stability, conditioning, and floating-point behavior impact models.
2025-09-02
Numerical Linear Algebra: Understanding Matrices and Vectors Through Computation
Learn how linear algebra actually works inside real computers. A practical guide to LU, QR, SVD, stability, conditioning, and the numerical foundations behind modern AI and machine learning.
2025-09-01
Teams App Manifest and Packaging|Mastering Microsoft Teams Bots 5.2
Transform your bot into a full Teams app. This section walks through how to create a Teams app manifest, add branding, define scopes, and package your bot into a distributable .zip file for sideloading, internal use, or submission to the Microsoft App Store.
2025-04-16
Localization and Multi-Tenant Support|Mastering Microsoft Teams Bots 4.4
Prepare your Microsoft Teams bot for real-world deployment. This section covers how to support multiple languages using localization, and how to safely handle multiple organizations with multi-tenant support — including tenant isolation, data security, and consent flows.
2025-04-14
Message Extensions|Mastering Microsoft Teams Bots 4.3
Learn how to build search- and action-based Message Extensions in Microsoft Teams. This section shows how to let users interact with your bot directly from the message composer — to search records, fill forms, or insert rich cards — all without leaving the chat.
2025-04-13
Proactive Messaging|Mastering Microsoft Teams Bots 4.2
Learn how to build bots that initiate conversations in Microsoft Teams. This section explains proactive messaging — including when and how to use it, how to store conversation references, and best practices to ensure your bot helps without interrupting.
2025-04-12
Conversation Flow and Dialogs|Mastering Microsoft Teams Bots 3.3
Learn how to build intelligent conversation flows in Microsoft Teams bots using dialogs. This section explains how to guide users through multi-turn interactions, manage state, use prompts and waterfalls, and decide when to use dialogs versus Task Modules.
2025-04-10
Message Handling|Mastering Microsoft Teams Bots 3.1
Learn how to build responsive and intelligent Microsoft Teams bots by handling messages effectively. This section covers activity types, keyword detection, mentions, markdown formatting, conversation context, and tips for scaling from simple replies to powerful, workflow-driven bots.
2025-04-08
Bot Authentication and Identity|Mastering Microsoft Teams Bots 2.3
Learn how Microsoft Teams bots authenticate users and access secure data. This section covers SSO, OAuth 2.0, and the Microsoft Graph API, giving your bot the ability to understand identity and act on behalf of users—safely and seamlessly.
2025-04-07
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
Overview of Microsoft Teams Bot Capabilities|Mastering Microsoft Teams Bots 1.3
Explore the full range of capabilities bots can offer in Microsoft Teams. This section breaks down interactive contexts, features like Adaptive Cards, proactive messaging, user authentication, Graph API integration, and what limitations still exist. Get a developer’s guide to what’s possible.
2025-04-04
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