Modern Keras The Comprehensive Guide to Deep Learning with the Keras API and Python
ISBN 978-1-4932-2739-6 500 pages, 2026
E-book formats: EPUB, PDF, online
ISBN 978-1-4932-2740-2 500 pages, 2026, Print edition paperback
E-book formats: EPUB, PDF, online
ISBN 978-1-4932-2741-9
- Learn to use Keras for deep learning
- Work with techniques such as gradient descent, classification, regularization, and more
- Build and train convolutional neural networks, transformers, and autoencoders
In this book, you'll learn about:
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Deep Learning Basics
Understand the foundations of deep learning, machine learning, and neural networks. Learn core concepts like gradient descent, classification, and regularization to fine-tune your models and minimize loss function.
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Model Development and Training
Follow step-by-step instructions to build models in Keras: develop a convolutional neural network, apply the functional API for complex models, and implement transformer architecture. Use reinforcement learning to improve your models’ decision-making.
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Generative AI Models
Build and train your own generative AI models! Get hands-on with text to image techniques and work with variational autoencoders and generative adversarial networks.
Highlights include:
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Neural networks
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Gradient descent
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Classification
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Regularization
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Convolutional neural networks (CNNs)
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Functional API
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Transformer architecture
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Reinforcement learning
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Autoencoders
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Stable Diffusion
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