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

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. Spis treści: 1. Introduction to Machine Learning with C++2. Data Processing3. Measuring Performance and Selecting Models4. Clustering5. Anomaly Detection6. Dimensionality Reduction7. Classification8. Recommender Systems9. Ensemble Learning10. Neural Networks for Image Classification11. Sentiment Analysis with BERT and Transfer Learning12. Exporting and Importing Models13. Tracking and Visualizing ML Experiments14. Deploying Models on a Mobile Platform O autorze: Kirill Kolodiazhnyi is a seasoned software engineer with expertise in custom software development. He has several years of experience building machine learning models and data products using C++. He holds a bachelor degree in Computer Science from the Kharkiv National University of Radio-Electronics. He currently works in Kharkiv, Ukraine where he lives with his wife and daughter.