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Evolutionary Deep Learning - Micheal Lanham

Evolutionary Deep Learning

(Autor)

Buch | Softcover
350 Seiten
2023
Manning Publications (Verlag)
978-1-61729-952-0 (ISBN)
CHF 89,95 inkl. MwSt
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.

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


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. about the technology Evolutionary deep learning merges the biology-simulating practices of evolutionary computation (EC) with the neural networks of deep learning. This unique approach can automate entire DL systems and help uncover new strategies and architectures. It gives new and aspiring AI engineers a set of optimization tools that can reliably improve output without demanding an endless churn of new data. about the reader For data scientists who know Python.  

Micheal Lanham  is a proven software and tech innovator with over 20 years of experience. He has developed a broad range of software applications in areas such as games, graphics, web, desktop, engineering, artificial intelligence, GIS, and machine learning applications for a variety of industries. At the turn of the millennium, Micheal began working with neural networks and evolutionary algorithms in game development.

Erscheinungsdatum
Verlagsort New York
Sprache englisch
Maße 185 x 236 mm
Gewicht 660 g
Themenwelt Mathematik / Informatik Informatik Software Entwicklung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
ISBN-10 1-61729-952-9 / 1617299529
ISBN-13 978-1-61729-952-0 / 9781617299520
Zustand Neuware
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