Mohammad Nauman: Modern Keras, Flexibler Einband

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Harness the power of AI with this guide to using Keras! Start by reviewing the fundamentals of deep learning and installing the Keras API. Next, follow Python code examples to build your own models, and then train them using classification, gradient descent, and regularization. Design large-scale, multilayer models and improve their decision making with reinforcement learning. With tips for creating generative AI models, this is your cutting-edge resource for working with deep learning!

Highlights include:

1. Neural networks
2. Gradient descent
3. Classification
4. Regularization
5. Convolutional neural networks (CNNs)
6. Functional API
7. Transformer architecture
8. Reinforcement learning
9. Autoencoders
10. Stable Diffusion