Advanced Deep Learning with Keras
This book covers advanced deep learning techniques to create successful AI. Using MLPs, CNNs, and RNNs as building blocks to more advanced techniques, you’ll study deep neural network architectures, Autoencoders, Generative Adversarial Networks (GANs), Variational AutoEncoders (VAEs), and Deep Reinforcement Learning (DRL) critical to many cutting-edge AI results.
Offered by
Difficulty Level
Intermediate
Completion Time
12h16m
Language
English
About Book
Who Is This Book For?
Some fluency with Python is assumed. As an advanced book, you'll be familiar with some machine learning approaches, and some practical experience with DL will be helpful. Knowledge of Keras or TensorFlow 1.x is not required but would be helpful.
Advanced Deep Learning with Keras
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 12h16m total length
Introducing Advanced Deep Learning with Keras
Deep Neural Networks
Autoencoders
Generative Adversarial Network (GANs)
Improved GANs
Disentangled Representation GANs
Cross-Domain GANs
Variational Autoencoders (VAEs)
Deep Reinforcement Learning
Policy Gradient Methods
Related Resources
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