Table of Contents

AI/ML Builder’s Companion Book (Vol. 2)

AI/ML Project Toolkit: Concepts & Tools Explained

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Contents

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📖 Preface

• Why This Book Exists
• Who Should Read This
• From Tutorials to Toolkits: How This Book Was Born
• What You’ll Learn (and What You Won’t)
• How to Read This Book (Even if You’re Just Starting Out)

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Part I – Development & Deployment Essentials

     Chapter 1: CI/CD: Continuous Integration & Deployment
     Chapter 2: FastAPI Explained
     Chapter 3: Gradio vs. React
     Chapter 4: Docker for AI Apps
     Chapter 5: .env Files & Secret Management
     Chapter 6: Railway, Hugging Face, and Render Compared

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Part II – AI/ML-Specific Tooling

     Chapter 7: What Is a GPU Runtime?
     Chapter 8: Transformers, Tokenizers & Hugging Face Ecosystem
     Chapter 9: Inference vs Training: Know the Difference
     Chapter 10: Understanding Replicate & Stability API
     Chapter 11: Prompt Engineering Basics

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Part III – Scalability, Monitoring & Security

     Chapter 12: Rate Limits, Cooldowns, and Billing Safety
     Chapter 13: Logging, Monitoring & Debugging
     Chapter 14: Authentication, Databases & User Management
     Chapter 15: CI/CD for Teams & SaaS-Ready Projects

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Part IV – Mindset & Philosophy

     Chapter 16: Why Tools Matter: Speed vs Reinvention
     Chapter 17: Shipping > Perfection: The Builder’s Ethos

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