(Ebook) Evolutionary Deep Learning (MEAP V11) by Michael Lanham ISBN 9781617299520, 1617299529

(Ebook) Evolutionary Deep Learning (MEAP V11) by Michael Lanham ISBN 9781617299520, 1617299529

Discover one-of-a-kind AI strategies never before seen outside of academic papers! Learn how the principles of evolutionary computation overcome deep learning’s common pitfalls and deliver adaptable model upgrades without constant manual adjustment. Evolutionary Deep Learning is a guide to improving your deep learning models with AutoML enhancements based on the principles of biological evolution. This exciting new approach utilizes lesser- known AI approaches to boost performance without hours of data annotation or model hyperparameter tuning. Google Colab notebooks make it easy to experiment and play around with each exciting example. By the time you’ve finished reading Evolutionary Deep Learning, you’ll be ready to build deep learning models as self-sufficient systems you can efficiently adapt to changing requirements. In Evolutionary Deep Learning you will learn how to:• Solve complex design and analysis problems with evolutionary computation• Tune deep learning hyperparameters with evolutionary computation (EC), genetic algorithms, and particle swarm optimization• Use unsupervised learning with a deep learning autoencoder to regenerate sample data• Understand the basics of reinforcement learning and the Q Learning equation• Apply Q Learning to deep learning to produce deep reinforcement learning• Optimize the loss function and network architecture of unsupervised autoencoders• Make an evolutionary agent that can play an OpenAI Gym game