Deep Learning in Practice, 9780367456580
Paperback
Master deep learning: build, optimize, and apply models in practice.

Deep Learning in Practice

$93.85

  • Paperback

    198 pages

  • Release Date

    1 December 2021

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Summary

Deep Learning in Practice: A Hands-On Guide

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 Network…

Book Details

ISBN-13:9780367456580
ISBN-10:0367456583
Author:Mehdi Ghayoumi
Publisher:Taylor & Francis Ltd
Imprint:Chapman & Hall/CRC
Format:Paperback
Number of Pages:198
Release Date:1 December 2021
Weight:400g
Dimensions:234mm x 156mm
About The Author

Mehdi Ghayoumi

Dr. Mehdi Ghayoumi is a course facilitator at Cornell University and adjunct faculty of Computer Science at the University of San Diego. Prior to this, he was a research assistant professor at SUNY at Binghamton, where he was the Media Core Lab’s dynamic leader. He was also a lecturer at Kent State University, where he received the Teaching Award for two consecutive years in 2016 and 2017. In addition, he has been teaching machine learning, data science, robotic and programming courses for several years.

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.

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