This is a comprehensive guide to the advanced deep learning techniques available today, so you can create your own cutting-edge AI. Using Keras as an open-source deep learning library, author Rowel Atienza shows hands-on projects demonstrating how to create more effective AI with the latest techniques. The book includes descriptions of GANs, Variational Autoencoders, and Deep Reinforcement Learning.
<ASIN:1788629418>
Author: Rowel Atienza Publisher: Packt Publishing Date: October 2018 Pages: 368 ISBN: 978-1788629416 Print: 1788629418 Kindle: B078N8RDCP Audience: Developers using Keras Level: Intermediate Category: Artificial Intelligence
Contents include
- Cutting-edge techniques in human-like AI performance
- Implement advanced deep learning models using Keras
- The building blocks for advanced techniques - MLPs, CNNs, and RNNs
- Deep neural networks – ResNet and DenseNet
- Autoencoders and Variational AutoEncoders (VAEs)
- Generative Adversarial Networks (GANs) and creative AI techniques
- Disentangled Representation GANs, and Cross-Domain GANs
- Deep Reinforcement Learning (DRL) methods and implementation
- Produce industry-standard applications using OpenAI gym
- Deep Q-Learning and Policy Gradient Methods
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