Deep Learning in Practice (ePub)
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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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.
Dr. Ghayoumi research interests are in Machine Learning, Machine Vision, Robotics, and Human-Robot Interaction (HRI). His research focuses are on building real systems for realistic environment settings, and his current projects have applications in Human-Robot Interaction, manufacturing, biometric, and healthcare.
He is a technical program committee member of several conferences, workshops, and editorial board member of several journals in machine learning, mathematics, and robotics, like ICML, ICPR, HRI, FG, WACV, IROS, CIBCB, and JAI. In addition, his research papers have been published at conferences and journals in the fields, including Human-Computer Interaction (HRI), Robotics Science and Systems (RSS), International Conference on Machine Learning and Applications (ICMLA), and others.
- Autor: Mehdi Ghayoumi
- 2021, 1. Auflage, 218 Seiten, Englisch
- Verlag: Taylor & Francis
- ISBN-10: 1000483398
- ISBN-13: 9781000483390
- Erscheinungsdatum: 30.11.2021
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: ePub
- Größe: 19 MB
- Ohne Kopierschutz
- Vorlesefunktion
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