Evolutionary Deep Learning – Genetic algorithms and neural networks – Manning Publications (2023)
English | Tutorial | Size: 56.91 MB
Discover one-of-a-kind AI strategies in Evolutionary Deep Learning, where evolutionary computation overcomes deep learning’s pitfalls and delivers adaptable model upgrades. Learn to solve complex problems, tune hyperparameters, use unsupervised learning, and apply Q-Learning for deep reinforcement learning, optimizing everything from data collection to network architecture.
What You Will Learn
Solve complex design and analysis problems with evolutionary computation
Tune deep learning hyperparameters with evolutionary computation, 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 for deep reinforcement learning
Optimize the loss function and network architecture of unsupervised autoencoders
Create an evolutionary agent that can play an OpenAI Gym game
About the Technology
Deep learning meets evolutionary biology in Evolutionary Deep Learning. Explore biology-inspired algorithms that amplify neural networks to solve complex search, optimization, and control problems, with practical examples demonstrating ancient lessons from nature shaping the cutting edge of data science.
About the Book
Evolutionary Deep Learning introduces evolutionary computation (EC), offering a toolbox of techniques applicable throughout the deep learning pipeline. Discover genetic algorithms, EC approaches to network topology, generative modeling, reinforcement learning, and more, with interactive Colab notebooks for experimentation.
What’s Inside
Solving complex design and analysis problems with evolutionary computation
Tuning deep learning hyperparameters
Applying Q-Learning for deep reinforcement learning
Optimizing loss function and network architecture of unsupervised autoencoders
Making an evolutionary agent for OpenAI Gym games
Target Audience
For data scientists familiar with Python.
About the Author
Micheal Lanham is a software and tech innovator with over 20 years of experience.
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