The book "Deep Learning Essentials: Concepts, Algorithms, and Techniques" provides a comprehensive introduction to the fundamental principles and methodologies of deep learning. It is designed for students, researchers, and professionals seeking to understand the theoretical foundations and practical implementations of modern neural network architectures. The book begins with an overview of machine learning basics, including supervised, unsupervised, and reinforcement learning, and then transitions into the core concepts of deep learning such as perceptrons, activation functions, and backpropagation. The book discusses techniques for regularization, hyperparameter tuning, and transfer learning, enabling efficient training and generalization.
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Paperback. Condición: new. Paperback. The book "Deep Learning Essentials: Concepts, Algorithms, and Techniques" provides a comprehensive introduction to the fundamental principles and methodologies of deep learning. It is designed for students, researchers, and professionals seeking to understand the theoretical foundations and practical implementations of modern neural network architectures. The book begins with an overview of machine learning basics, including supervised, unsupervised, and reinforcement learning, and then transitions into the core concepts of deep learning such as perceptrons, activation functions, and backpropagation. The book discusses techniques for regularization, hyperparameter tuning, and transfer learning, enabling efficient training and generalization. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9786207469628
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book 'Deep Learning Essentials: Concepts, Algorithms, and Techniques' provides a comprehensive introduction to the fundamental principles and methodologies of deep learning. It is designed for students, researchers, and professionals seeking to understand the theoretical foundations and practical implementations of modern neural network architectures. The book begins with an overview of machine learning basics, including supervised, unsupervised, and reinforcement learning, and then transitions into the core concepts of deep learning such as perceptrons, activation functions, and backpropagation. The book discusses techniques for regularization, hyperparameter tuning, and transfer learning, enabling efficient training and generalization.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch. Nº de ref. del artículo: 9786207469628
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