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:
- D emonstrates a quick review on Python, Num Py, and Tensor Flow fundamentals.
- E xplains and provides examples of deploying Tensor Flow and Keras in several projects.
- E xplains the fundamentals of Artificial Neural Networks (ANNs).
- P resents several examples and applications of ANNs.
- L earning the most popular DL algorithms features.
- E xplains and provides examples for the DL algorithms that are presented in this book.
- A nalyzes the DL network’s parameter and hyperparameters.
- R eviews state-of-the-art DL examples.
- N ecessary and main steps for DL modeling.
- I mplements a Virtual Assistant Robot (VAR) using DL methods.
- N ecessary and fundamental information to choose a proper DL algorithm.
- G ives 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.
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Format EPUB ● Pages 218 ● ISBN 9781000483390 ● Maison d’édition CRC Press ● Publié 2021 ● Téléchargeable 3 fois ● Devise EUR ● ID 8171926 ● Protection contre la copie Adobe DRM
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