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Evolutionary deep learning : genetic algorithms and neural networks /
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....
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Shelter Island, NY :
Manning Publications,
2023.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
| LEADER | 00000cam a22000007i 4500 | ||
|---|---|---|---|
| 001 | OR_on1396224086 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 230906s2023 nyua o 001 0 eng d | ||
| 040 | |a ORMDA |b eng |e rda |e pn |c ORMDA |d EBLCP | ||
| 020 | |a 9781617299520 |q (electronic bk.) | ||
| 020 | |a 1617299529 |q (electronic bk.) | ||
| 020 | |z 1617299529 | ||
| 035 | |a (OCoLC)1396224086 | ||
| 037 | |a 9781617299520 |b O'Reilly Media | ||
| 050 | 4 | |a Q325.73 | |
| 082 | 0 | 4 | |a 006.3/1 |2 23/eng/20230906 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Lanham, Micheal, |e author. |1 https://isni.org/isni/0000000500215498 | |
| 245 | 1 | 0 | |a Evolutionary deep learning : |b genetic algorithms and neural networks / |c Micheal Lanham. |
| 264 | 1 | |a Shelter Island, NY : |b Manning Publications, |c 2023. | |
| 300 | |a 1 online resource (xxii, 336 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 500 | |a Includes index. | ||
| 520 | |a 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. In this one-of-a-kind guide, you’ll discover tools for optimizing everything from data collection to your network architecture. | ||
| 505 | 0 | |a Part 1. Getting started. Introducing evolutionary deep learning -- Introducing evolutionary computation -- Introducing genetic algorithms with DEAP -- More evolutionary computation with DEAP -- Part 2. Optimizing deep learning. Automating hyperparameter optimization -- Neuroevolution optimization -- Evolutionary convolutional neural networks -- Part 3. Advanced applications. Evolving autoencoders -- Generative deep learning and evolution -- NEAT: neuroEvolution of augmenting topologies -- Evolutionary learning with NEAT -- Evolutionary machine learning and beyond. | |
| 588 | |a Description based on print version record. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Deep learning (Machine learning) | |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Evolutionary computation. | |
| 655 | 0 | |a Electronic books. | |
| 776 | 0 | 8 | |i Print version: |a Lanham, Micheal. |t Evolutionary deep learning. |d Shelter Island, NY : Manning Publications, 2023 |z 9781617299520 |w (OCoLC)1390609254 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781617299520/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL30666116 | ||
| 994 | |a 92 |b IZTAP | ||