Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines , Second Edition

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Key benefits

Familiarize yourself with data processing, performance measuring, and model selection using various C++ libraries

Implement practical machine learning and deep learning techniques to build smart models

Deploy machine learning models to work on mobile and embedded devices

Purchase of the print or Kindle book includes a free PDF eBook

Description

Written by a seasoned software engineer with several years of industry experience, this book will teach you the basics of machine learning (ML) and show you how to use C++ libraries, along with helping you create supervised and unsupervised ML models. You’ll gain hands-on experience in tuning and optimizing a model for various use cases, enabling you to efficiently select models and measure performance. The chapters cover techniques such as product recommendations, ensemble learning, anomaly detection, sentiment analysis, and object recognition using modern C++ libraries. You’ll also learn how to overcome production and deployment challenges on mobile platforms, and see how the ONNX model format can help you accomplish these tasks. This new edition has been updated with key topics such as sentiment analysis implementation using transfer learning and transformer-based models, as well as tracking and visualizing ML experiments with MLflow. An additional section shows you how to use Optuna for hyperparameter selection. The section on model deployment into mobile platform now includes a detailed explanation of real-time object detection for Android with C++. By the end of this C++ book, you’ll have real-world machine learning and C++ knowledge, as well as the skills to use C++ to build powerful ML systems.

What you will learn

Employ key machine learning algorithms using various C++ libraries

Load and pre-process different data types to suitable C++ data structures

Find out how to identify the best parameters for a machine learning model

Use anomaly detection for filtering user data

Apply collaborative filtering to manage dynamic user preferences

Utilize C++ libraries and APIs to manage model structures and parameters

Implement C++ code for object detection using a modern neural network

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

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Unfortunately, due to several restrictions, we are unable to ship to the following countries:

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Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines , Second Edition

What do you get with Print?