{R}R 開発ノート
合計 74 件の記事が見つかりました。
Art of Coding, Chapter 11: Architectural Thinking
Architectural thinking is the discipline of designing systems that survive real-world growth. It means asking how your code will feel to live in years from now.
2026-01-06
Art of Coding, Chapter 10: Anti-Patterns to Avoid
Anti-patterns are the structural traps that silently erode codebases. Learning to recognize them early is one of the most valuable skills a developer can have.
2026-01-05
Art of Coding, Chapter 9: Design Patterns as a Language of Developers
Design patterns compress complex architectural ideas into shared language. But they're tools for solving problems, not decorations for code.
2026-01-04
Art of Coding, Part IV: Patterns, Anti-Patterns, and Architecture
Part IV explores design patterns as language, anti-patterns as warning signs, and architecture as the invisible skeleton enabling system growth.
2026-01-03
Art of Coding, Chapter 8: Performance without Sacrificing Clarity
Chasing speed too early blinds you to real bottlenecks. Clarity first, measurement second, optimization third—that's the order.
2026-01-02
Art of Coding, Chapter 7: Error Handling and Resilience
Designing for failure, not avoiding it. How graceful error handling, clear logging, and balanced defense build systems that endure.
2026-01-01
Art of Coding, Chapter 6: Abstraction and Modularity
Drawing boundaries that make systems stronger. How to abstract without over-engineering, and design interfaces that last.
2025-12-31
Art of Coding, Chapter 5: Consistency and Style
Consistency is kindness. How coding standards, formatters, and idiomatic style shape code that teams can actually live with.
2025-12-29
Art of Coding, Chapter 4: Maintainability and Scalability
How to build code that bends instead of breaks, systems that grow without collapsing, and anticipate change without over-engineering.
2025-12-28
Art of Coding, Part II: Principles of Clarity
Part II introduces clarity as the compass of software: readability, maintainability, and the consistency that makes teams move faster.
2025-12-26
Art of Coding, Chapter 2: The Philosophy of Clean Code
Clean code is a philosophy, not a rulebook. Explore simplicity vs. cleverness, expressiveness as communication, and code as a form of writing.
2025-12-25
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
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
4.3 Pivoting Strategies
A practical and intuitive guide to pivoting strategies in numerical linear algebra, explaining partial, complete, and scaled pivoting and why pivoting is essential for stable Gaussian elimination and reliable LU decomposition.
2025-09-20
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
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
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
1.3 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
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
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
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
カテゴリー
タグ
検索ログ
Hello World bot 927
Deploy Teams bot to Azure 862
IT assistant bot 862
Microsoft Bot Framework 839
Azure CLI webapp deploy 812
Adaptive Card Action.Submit 768
Teams bot development 763
Bot Framework Adaptive Card 744
Adaptive Cards 739
Bot Framework example 737
Microsoft Graph 737
Microsoft Teams Task Modules 735
Teams app zip 733
Graph API token 732
Teams bot packaging 723
Teams production bot 723
C 717
Teams bot tutorial 717
Zendesk Teams integration 717
Task Modules 715
Azure Bot Services 713
Azure App Service bot 711
bot for sprint updates 711
Teams chatbot 707
Bot Framework CLI 700
ServiceNow bot 700
Bot Framework proactive messaging 698
Azure bot registration 697
Bot Framework prompts 695
proactive messages 682
Development & Technical Consulting
Working on a new product or exploring a technical idea? We help teams with system design, architecture reviews, requirements definition, proof-of-concept development, and full implementation. Whether you need a quick technical assessment or end-to-end support, feel free to reach out.
Contact Us