دانلود کتاب دستی بر یادگیری ماشین با ++C

C++ can make your machine learning (ML) models run faster and more efficiently. This book teaches you the basics of ML and shows you how to use C++ libraries. It explains how to create supervised and unsupervised ML models.
You’ll get hands-on with tuning and optimizing a model for different use cases, assisting you with model selection and the measurement of performance. The book covers techniques such as product recommendations, ensemble learning, anomaly detection, sentiment analysis, and object recognition using modern C++ libraries. Further, you’ll learn how to handle production and deployment challenges on mobile platforms, and how the ONNX model format can help you in such tasks.
This new edition is updated with key topics such as sentiment analysis implementation using transfer learning and transformer-based models and tracking and visualizing ML experiments with MLflow. Also, there is an additional section about using Optuna for hyperparameter selection. The section about model deployment into mobile platforms is extended with a detailed explanation of real-time object detection for Android with C++.
By the end of this C++ book, you will have real-world ML and C++ knowledge, as well as the skills to use C++ to build powerful ML systems.
If you want to get started with ML algorithms and techniques using the popular C++ language, then this book is for you. Aside from being a useful first course in ML with C++, this book will also appeal to data analysts, data scientists, and ML developers looking to implement different ML models in production using C++, which can be useful for some specific platforms, for example, embedded devices. Working knowledge of the C++ programming language, linear algebra, and basic calculus understanding are needed to get started with this book.