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Deep Learning in Practice.

Deep Learning in Practice.

・ISBN 978-0-367-45862-1 hard GB£ 82.99

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お気に入り
電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 9781003025818
著者・編者Ghayoumi, Mehdi,
出版社 (Chapman & Hall/CRC, UK)
出版年月2021
ページ数198 pp.
言語ENG
ニュース番号<A00-45858>

解説

Deep Learning in Practice helps you learn how to develop and optimize a model for your projects using Deep Learning (DL) methods and architectures.

Key features:

  • Demonstrates a quick review on Python, NumPy, and TensorFlow fundamentals.
  • Explains and provides examples of deploying TensorFlow and Keras in several projects.
  • Explains the fundamentals of Artificial Neural Networks (ANNs).
  • Presents several examples and applications of ANNs.
  • Learning the most popular DL algorithms features.
  • Explains and provides examples for the DL algorithms that are presented in this book.
  • Analyzes the DL network's parameter and hyperparameters.
  • Reviews state-of-the-art DL examples.
  • Necessary and main steps for DL modeling.
  • Implements a Virtual Assistant Robot (VAR) using DL methods.
  • Necessary and fundamental information to choose a proper DL algorithm.
  • Gives instructions to learn how to optimize your DL model IN PRACTICE.

This book is useful for undergraduate and graduate students, as well as practitioners in industry and academia. It will serve as a useful reference for learning deep learning fundamentals and implementing a deep learning model for any project, step by step.