Modern deep learning design and application development versatile tools to solve deep learning problems
Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learnin...
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| Format: | eBook |
| Language: | Inglés |
| Published: |
New York, New York :
Apress
[2022]
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| See on Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009638339606719 |
Table of Contents:
- Chapter 1: A Deep Dive Into Keras
- Chapter 2: Pre-training Strategies and Transfer Learning
- Chapter 3: The Versatility of Autoencoders
- Chapter 4: Model Compression for Practical Deployment
- Chapter 5: Automating Model Design with Meta-Optimization
- Chapter 6:Successful Neural Network Architecture Design
- Chapter 7:Reframing Difficult Deep Learning Problems.
