{R}R Dev Notes


Found total of 70 articles.

Art of Coding, Chapter 1: Code That Speaks

Chapter 1 of the Art of Coding series. Why beauty in code is not decoration but survival — clarity, empathy, efficiency, and what separates code that works from code that lasts. Plus: what AI-generated code means for craftsmanship.
2025-12-24

Art of Coding, Part I: Why Code is an Art

Introducing the Art of Coding blog series: a 26-week exploration of what makes code beautiful, maintainable, and enduring in the age of AI.
2025-12-23

8.4 PCA and Spectral Methods

An intuitive, in-depth explanation of PCA, spectral clustering, and eigenvector-based data analysis. Covers covariance matrices, graph Laplacians, and why eigenvalues reveal hidden structure in data. Concludes Chapter 8 and leads naturally into SVD in Chapter 9.
2025-10-10

8.1 Power Method and Inverse Iteration

A clear, practical, and intuitive explanation of the power method and inverse iteration for computing eigenvalues. Covers dominance, repeated multiplication, shifted inverse iteration, and real applications in ML, PCA, and large-scale systems. Smoothly introduces the Rayleigh quotient.
2025-10-07

Chapter 6 — Cholesky Decomposition

A deep, narrative-driven introduction to Cholesky decomposition explaining why symmetric positive definite matrices dominate real computation. Covers structure, stability, performance, and the role of Cholesky in ML, statistics, and optimization.
2025-09-27

5.4 Practical Examples

Hands-on LU decomposition examples using NumPy and LAPACK. Learn how pivoting, numerical stability, singular matrices, and performance optimization work in real systems, with clear Python code and practical insights.
2025-09-26

5.3 LU in NumPy and LAPACK

A practical, in-depth guide to how LU decomposition is implemented in NumPy and LAPACK. Learn about partial pivoting, blocked algorithms, BLAS optimization, error handling, and how modern numerical libraries achieve both speed and stability.
2025-09-25

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

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

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

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

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

Use Case: Sales Assistant Bot|Mastering Microsoft Teams Bots 6.3

Learn how to build a Sales Assistant Bot for Microsoft Teams. From surfacing leads to logging calls and syncing with CRMs, this section shows how bots can empower sales teams to move faster, close deals, and automate follow-ups — all within Teams.
2025-04-20

Use Case: Project Management Assistant Bot|Mastering Microsoft Teams Bots 6.2

Explore how to build a Project Management Assistant Bot for Microsoft Teams that delivers task summaries, reminders, and updates directly in the chat. Learn how this bot improves team productivity by integrating with tools like Jira or Trello and surfacing key information within the Teams workflow.
2025-04-19

Use Case: Helpdesk Assistant Bot|Mastering Microsoft Teams Bots 6.1

Explore how to build a Helpdesk Assistant Bot in Microsoft Teams. Learn how bots can reduce IT load by handling FAQs, logging support tickets, and notifying users — all within Teams. This section explains features, user experience, and implementation strategies.
2025-04-18

Monitoring, Logging, and Telemetry|Mastering Microsoft Teams Bots 5.3

Learn how to monitor and support your Microsoft Teams bot in production using logging, Azure Application Insights, and alerts. This section shows how to track user events, diagnose failures, and create telemetry that makes your bot reliable and supportable.
2025-04-17

Rich Responses with Adaptive Cards|Mastering Microsoft Teams Bots 3.2

Learn how to create rich, interactive messages in Microsoft Teams using Adaptive Cards. This section explains how to design, send, and handle cards in your bot — making your bot feel less like a chat and more like a true app experience inside Teams.
2025-04-09

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

Mastering Microsoft Teams Bots: A Complete Developer’s Guide

The definitive guide to building bots for Microsoft Teams—from fundamentals to deployment. Learn how to build intelligent and interactive bots using the Microsoft Bot Framework, integrate Adaptive Cards and Task Modules, send proactive messages, authenticate users with Teams SSO, and deploy securely on Azure. Packed with practical examples and real-world use cases, this book will help you automate workflows, enhance collaboration, and deliver smart experiences inside Teams.
2025-04-01