
Deep Learning in Practice
$93.85
- Paperback
198 pages
- Release Date
1 December 2021
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 |
You Can Find This Book In
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.
Returns
This item is eligible for free returns within 30 days of delivery. See our returns policy for further details.