Description: About this Item The item is a book Paperback The Author Name is Micheal Lanham The Title is Evolutionary Deep Learning Condition New Other Comments Pages Count - 350. Category - Computers Product Description - 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 computationTune deep learning hyperparameters with evolutionary computation EC, genetic algorithms, and particle swarm optimizationUse unsupervised learning with a deep learning autoencoder to regenerate sample dataUnderstand the basics of reinforcement learning and the Q Learning equationApply Q Learning to deep learning to produce deep reinforcement learningOptimize the loss function and network architecture of unsupervised autoencodersMake 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. We Use Stock Images Because we have over 2 million items for sale we have to use stock images, this listing does not include the actual image of the item for sale. The purchase of this specific item is made with the understanding that the image shown in this listing is a stock image and not the actual item for sale. For example: some of our stock images include stickers, labels, price tags, hyper stickers, obi's, promotional messages, signatures and or writing which may not be available in the actual item. When possible we will add details of the items we are selling to help buyers know what is included in the item for sale. The details  are provided automatically  from our central master database and can sometimes be wrong. Books are released in many editions and variations, such as standard edition, re-issue, not for sale, promotional, special edition, limited edition, and many other editions and versions.  The Book you receive could be any of these editions or variations. If you are looking for a specific edition or version please contact us to verify what we are selling.   Gift IdeasThis is a  great Christmas gift idea.   Hours of ServiceWe have many warehouses,  some of the warehouses process orders seven days a week, but the Administration Support Staff are located at a head office location, outside of the warehouses, and typically work only Monday to Friday. Location ID 9000z iHaveit SKU ID 167557609
Price: 82.53 USD
Location: US
End Time: 2024-12-22T13:03:11.000Z
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
Fiction/Non-Fiction: Non-Fiction
Genre/Subject: Computers
Brand: Manning Publications
Weight: 0.55
Style: NA
Title: Evolutionary Deep Learning
Release Title: Evolutionary Deep Learning
Record Grading: New
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Film/TV Title: Evolutionary Deep Learning
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Number of Pages: 350 Pages
Publication Name: Evolutionary Deep Learning
Language: English
Publisher: Manning Publications Co. LLC
Item Height: 0.7 in
Publication Year: 2023
Subject: Neural Networks, Data Processing
Item Weight: 23.3 Oz
Type: Textbook
Item Length: 9.3 in
Author: Micheal Lanham
Subject Area: Computers
Item Width: 7.3 in
Format: Trade Paperback