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Fakta
"Mastering Deep Learning with Keras: From Basics to Expert Proficiency" is an authoritative guide to the world of deep learning, meticulously designed for both beginners and experienced practitioners. This comprehensive book embarks on a detailed exploration of deep learning concepts, starting with foundational principles and progressively advancing to complex techniques and real-world applications. By leveraging the simplicity and flexibility of the Keras framework, readers are equipped with practical skills to build, train, and deploy state-of-the-art neural network models effectively.
The book is structured into well-organized chapters that cover every crucial area of deep learning, from neural network fundamentals and handling image and textual data, to advanced architectures, hyperparameter tuning, and model evaluation. Special emphasis is placed on practical implementations, ensuring readers can seamlessly translate theory into practice. Additionally, the nuanced discussion on cutting-edge topics like GANs, transformers, and model deployment on cloud platforms positions this book as an indispensable resource for mastering deep learning with Keras. Whether you are a novice eager to understand the basics or an expert looking to refine your knowledge, this book offers a thorough and accessible path to deep learning proficiency.
© 2024 HiTeX Press (E-bog): 6610000623310
Release date
E-bog: 11. august 2024
Fakta
"Mastering Deep Learning with Keras: From Basics to Expert Proficiency" is an authoritative guide to the world of deep learning, meticulously designed for both beginners and experienced practitioners. This comprehensive book embarks on a detailed exploration of deep learning concepts, starting with foundational principles and progressively advancing to complex techniques and real-world applications. By leveraging the simplicity and flexibility of the Keras framework, readers are equipped with practical skills to build, train, and deploy state-of-the-art neural network models effectively.
The book is structured into well-organized chapters that cover every crucial area of deep learning, from neural network fundamentals and handling image and textual data, to advanced architectures, hyperparameter tuning, and model evaluation. Special emphasis is placed on practical implementations, ensuring readers can seamlessly translate theory into practice. Additionally, the nuanced discussion on cutting-edge topics like GANs, transformers, and model deployment on cloud platforms positions this book as an indispensable resource for mastering deep learning with Keras. Whether you are a novice eager to understand the basics or an expert looking to refine your knowledge, this book offers a thorough and accessible path to deep learning proficiency.
© 2024 HiTeX Press (E-bog): 6610000623310
Release date
E-bog: 11. august 2024
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