Hands-On Machine Learning with C++ : Build, train, and deploy end-to-end machine learning and deep learning pipelines (2 Revised edition)

Implement supervised and unsupervised machine learning (ML) algorithms using C++ libraries such as PyTorch C++ API, TensorFlow C++ API, Flashlight, mlpack, and dlib with the help of real-world examples and datasetsKey FeaturesFamiliarize yourself with data processing, performance measuring, and model selection using various C++ librariesImplement practical machine learning and deep learning techniques to build smart modelsDeploy machine learning models to work on mobile and embedded devicesPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionC++ can make your machine learning models run faster and more efficiently.

This handy guide will help you learn the fundamentals of machine learning, showing you how to use C++ libraries to get the most out of your data.

This book makes machine learning with C++ for beginners easy with its example-based approach, demonstrating how to implement supervised and unsupervised ML algorithms through real-world examples. You’ll get hands-on experience with tuning and optimizing a model for different use cases, and get to grips with model selection and the measurement of performance.

Next, you’ll cover techniques such as product recommendations, ensemble learning, anomaly detection, sentiment analysis, and object recognition using modern C++ libraries such as PyTorch C++ API, TensorFlow C++ API, Flashlight, mlpack, and dlib.

You’ll also explore neural networks, deep learning, and transfer learning that allows you to use pre-trained models.

The later chapters will teach you how to handle production and deployment challenges on mobile and cloud platforms, and how the ONNX model format can help you with such tasks.

You’ll also learn how to extend existing deep learning frameworks with new operations. By the end of this book, you will have real-world ML and C++ knowledge, as well as the skills to use C++ to build powerful ML systems.What you will learnFind out how to load and pre-process various data types to suitable C++ data structuresEmploy key machine learning algorithms with various C++ librariesUnderstand how to find the best parameters for a machine learning modelUse anomaly detection for filtering user dataApply collaborative filtering to deal with dynamic user preferencesUse C++ libraries and APIs to manage model structures and parametersBuild a C++ program for object detection with advanced neural networksExtend machine learning frameworks with custom operators written in C++Who this book is forIf you want to get started with machine learning algorithms and techniques using the popular C++ language, then this C++ machine learning book is for you.

Aside from being a useful first course in machine learning with C++, this book will also appeal to data analysts, data scientists, and machine learning developers looking to implement different machine learning models in production using varied datasets and examples.

Working knowledge of the C++ programming language is needed to get started with this book.