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    Python Deep Learning. Understand how deep neural networks work and apply them to real-world tasks - Third Edition Ivan Vasilev

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Python Deep Learning. Understand how deep neural networks work and apply them to real-world tasks - Third Edition Ivan Vasilev - okladka książki

    Python Deep Learning. Understand how deep neural networks work and apply them to real-world tasks - Third Edition Ivan Vasilev - okladka książki

    Python Deep Learning. Understand how deep neural networks work and apply them to real-world tasks - Third Edition Ivan Vasilev - audiobook MP3

    Python Deep Learning. Understand how deep neural networks work and apply them to real-world tasks - Third Edition Ivan Vasilev - audiobook CD

    Autor:
    Ivan Vasilev
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    362
    Dostępne formaty:
         PDF
         ePub
    The field of deep learning has developed rapidly recently and today covers a broad range of applications. This makes it challenging to navigate and hard to understand without solid foundations. This book will guide you from the basics of neural networks to the state-of-the-art large language models in use today.
    The first part of the book introduces the main machine learning concepts and paradigms. It covers the mathematical foundations, the structure, and the training algorithms of neural networks and dives into the essence of deep learning.
    The second part of the book introduces convolutional networks for computer vision. We’ll learn how to solve image classification, object detection, instance segmentation, and image generation tasks.
    The third part focuses on the attention mechanism and transformers – the core network architecture of large language models. We’ll discuss new types of advanced tasks they can solve, such as chatbots and text-to-image generation.
    By the end of this book, you’ll have a thorough understanding of the inner workings of deep neural networks. You'll have the ability to develop new models and adapt existing ones to solve your tasks. You’ll also have sufficient understanding to continue your research and stay up to date with the latest advancements in the field.

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    O autorze książki

    Ivan Vasilev started working on the first open source Java deep learning library with GPU support in 2013. The library was acquired by a German company, where he continued to develop it. He has also worked as a machine learning engineer and researcher in the area of medical image classification and segmentation with deep neural networks. Since 2017, he has been focusing on financial machine learning. He is working on a Python-based platform that provides the infrastructure to rapidly experiment with different machine learning algorithms for algorithmic trading. Ivan holds an MSc degree in artificial intelligence from the University of Sofia, St. Kliment Ohridski.

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