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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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Ye, Andre (Author)
Format: Electronic eBook
Language:Inglés
Published: [New York, NY] : Apress, 2022.
Subjects:
Deep learning (Machine learning)
Apprentissage profond.
Online Access:Texto completo (Requiere registro previo con correo institucional)
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.

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