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The Deep Learning with PyTorch Workshop

You're reading from The Deep Learning with PyTorch Workshop Build deep neural networks and artificial intelligence applications with PyTorch

Product type Paperback

Published in Jul 2020

Publisher Packt

ISBN-13 9781838989217

Length 330 pages

Edition 1st Edition

Languages

Python

Tools

PyTorch

Concepts

Artificial Intelligence

Author (1):

Hyatt Saleh

View More author details

Table of Contents (8) Chapters

Preface

1. Introduction to Deep Learning and PyTorch

2. Building Blocks of Neural Networks FREE CHAPTER

3. A Classification Problem Using DNN

4. Convolutional Neural Networks

5. Style Transfer

6. Analyzing the Sequence of Data with RNNs

Appendix

5. Style Transfer

Overview

This chapter explains the process of using pre-trained models in order to create or make use of well-performing algorithms without having to gather large quantities of data. In this chapter, you will learn how to load a pre-trained model from PyTorch in order to create a style transfer model. By the end of this chapter, you will be able to perform style transfer through the use of pretrained models.

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Authors (1)

Hyatt Saleh

Hyatt Saleh

Hyatt Saleh discovered the importance of data analysis for understanding and solving real-life problems after graduating from college as a business administrator. Since then, as a self-taught person, she not only works as a machine learning freelancer for many companies globally, but has also founded an artificial intelligence company that aims to optimize everyday processes. She has also authored Machine Learning Fundamentals, by Packt Publishing.

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