Publisher's Synopsis
Build Fast, Reliable AI Systems from Code to Deployment
Looking to master machine learning in C++-without getting lost in theory?
This book makes advanced AI approachable. It explains every concept in clear, plain language-while providing serious technical depth through rigorous exercises, real-world projects, and expert-level code samples. You'll gain the clarity of a beginner-friendly guide with the challenge of a professional-grade resource.
Inside, You'll Learn How To:
Build machine learning models using TensorFlow's powerful C++ API
Implement core algorithms: regression, trees, neural networks, reinforcement learning
Work with real data in computer vision, natural language processing, and time series
Optimize models for speed, memory, and deployment on edge devices
Deploy full ML pipelines into production with C++ and TensorFlow
What Makes This Book Different:
Easy to read: complex ideas broken down step-by-step
Hard to master: advanced exercises and deep implementation challenges
Over 100 TensorFlow C++ code examples you can run, adapt, and scale
Visual infographics make concepts click instantly
Case studies show you how it all works in the real world
Whether you're a C++ developer new to AI, or an ML engineer ready to push beyond Python, this book gives you the tools-and the challenge-to build production-grade machine learning systems.
Get ready to learn fast. Then build faster.
