 Название: C++ for Machine Learning: A Comprehensive Programming Guide
Автор: Hayden Van Der Post
Издательство: Reactive Publishing
Год: 2025
Страниц: 590
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB
C++ for Machine Learning.
Build Lightning-Fast AI Systems with the Power of Native Code.
Discover the full potential of artificial intelligence by harnessing the speed, precision, and control of C++. While most Machine Learning resources stop at Python, this groundbreaking guide goes deeper—showing you how to build high-performance ML models and systems from the ground up using one of the world’s fastest programming languages.
Machine Learning is at the heart of tomorrow’s breakthroughs, and C++ stands out as the language that not only meets but exceeds these demands. Renowned for its speed, control, and versatility, C++ empowers you to build high-performance models and robust applications that can tackle real-world challenges—from analyzing big data to driving autonomous systems. This book is crafted to show you how to harness that power.
Throughout these pages, you will explore a comprehensive curriculum that begins with the fundamentals of C++ and gently escalates to advanced topics like neural networks, Deep Learning, and even reinforcement learning. Each chapter is designed to offer practical, step-by-step guidance with clear code examples and real-world applications. We start by laying a solid foundation with the basics of Machine Learning and C++ programming, ensuring that you feel confident as you progress to complex topics like optimization techniques, natural language processing, and computer vision. Every concept, every algorithm, and every tool is presented in a way that inspires not only learning but innovation.
Designed for engineers, researchers, and developers ready to break out of the limitations of interpreted languages, this book covers:
Core ML concepts implemented directly in C++
Efficient data structures, matrix operations, and memory management
Building neural networks without relying on heavy libraries
Integrating C++ with CUDA and OpenCL for GPU acceleration
Bridging C++ with Python for hybrid workflows
Deployment strategies for production-grade AI applications
Whether you're optimizing inference times, developing edge AI solutions, or building custom learning algorithms, C++ for Machine Learning gives you the toolkit to own the entire stack—from data to decision.
This isn’t another beginner’s ML book. It’s a weapon for those ready to go beyond the black box—and build AI systems that are fast, powerful, and deeply yours.
Contents:
Preface
Chapter 1: Overview of Machine Learning
Chapter 2: C++ Fundamentals Refresher
Chapter 3: Math and Statistics for Machine Learning
Chapter 4: Data Preprocessing in C++
Chapter 5: Regression Analysis with C++
Chapter 6: Classification Techniques in C++
Chapter 7: Unsupervised Learning and Clustering
Chapter 8: Neural Networks from Scratch
Chapter 9: Deep Learning and Frameworks in C++
Chapter 10: Reinforcement Learning Basics
Chapter 11: Optimization Techniques in C++
Chapter 12: Working with Large Data Sets
Chapter 13: Natural Language Processing in C++
Chapter 14: Computer Vision Techniques
Chapter 15: Model Evaluation and Validation
Chapter 16: Deployment of Machine Learning Models
Chapter 17: Emerging Trends and Future Directions in Machine Learning
with C++
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C++ for Machine Learning: A Comprehensive Programming Guide 
