develop machine learning and deep learning models with Python Raschka, Sebastian creator Liu, Yuxi Mirjalili, Vahid Dzhulgakov, Dmytro text Birmingham Packt Publishing 2022 monographic eng

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xxix, 741 p. "Machine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and examples, this book covers all the essential machine learning techniques in depth. While some books teach youonly to follow instructions, with this machine learning book, we teach you the principles to build models and applications for yourself. Updated to cover deep learning using PyTorch, this book also introduces readers to the latest additions to scikit-learn. Moreover, this book covers various machine learning and deep learning techniques for text and image classification. You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is also expanded to cover the latest trends in deep learning, including introductions to graph neural networks and large-scale transformers used for natural language processing (NLP). This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments" -- From back cover Sebastian Raschka, Yuxi Liu and Vahid Mirjalili ; foreword by Dmytro Dzhulgakov Index present Eng Machine learning Artificial intelligence Deep learning Python (computer program language) 006.31 RAS-M 9781801819312 260605 20260605142941.0