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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

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Autor:
    Kirill Kolodiazhnyi
    Hands-On Machine Learning with C++. Build, train, and deploy end-to-end machine learning and deep learning pipelines - Second Edition Kirill Kolodiazhnyi - okladka książki

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

    Hands-On Machine Learning with C++. Build, train, and deploy end-to-end machine learning and deep learning pipelines - Second Edition Kirill Kolodiazhnyi - audiobook MP3

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

    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Stron:
    78
    C++ 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.

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    O autorze książki

    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.

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