Deep Learning in Practice, 1st Edition

Deep Learning in Practice By Mehdi Ghayoumi
English | 2021 | ISBN: 0367458624 | 219 pages | True PDF| 40.74 MB


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:

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[*]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.

[/list]

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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