Deep Learning from the Basics: Python and Deep Learning: Theory and Implementation

Koki Saitoh

ISBN 10: 1800206135 / ISBN 13: 9781800206137

Published by Packt Publishing Limited, 2021

About this Item

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Bibliographic Details

• Title: Deep Learning from the Basics: Python and Deep Learning: Theory and Implementation
• Publisher: Packt Publishing Limited
• Publication Date: 2021
• Language: English
• ISBN 10: 1800206135
• ISBN 13: 9781800206137
• Binding: Paperback / softback
• Condition: New

About this title

Synopsis

Deep learning is rapidly becoming the most preferred way of solving data problems. This is thanks, in part, to its huge variety of mathematical algorithms and their ability to find patterns that are otherwise invisible to us.

Deep Learning from the Basics begins with a fast-paced introduction to deep learning with Python, its definition, characteristics, and applications. You'll learn how to use the Python interpreter and the script files in your applications, and utilize NumPy and Matplotlib in your deep learning models. As you progress through the book, you'll discover backpropagation-an efficient way to calculate the gradients of weight parameters-and study multilayer perceptrons and their limitations, before, finally, implementing a three-layer neural network and calculating multidimensional arrays.

By the end of the book, you'll have the knowledge to apply the relevant technologies in deep learning.

About the Author

Koki Saitoh was born in Tsushima, Nagasaki in 1984. He graduated from the engineering department of the Tokyo Institute of Technology and completed a master’s course at the Graduate School of Interdisciplinary Information Studies at the University of Tokyo. Currently, he conducts research and development in computer vision and machine learning. He has authored Python 3 in Practice, The Elements of Computing Systems, and Building Machine Learning Systems with Python, translations of which are published by O’Reilly, Japan.