The Deep Learning with PyTorch Workshop: Build deep neural networks and artificial intelligence applications with PyTorch
by: Hyatt Saleh Print Length 页数: 330 pages
Publisher finelybook 出版社: Packt Publishing (22 July 2020)
Language 语言: English
ISBN-10: 1838989218
ISBN-13: 9781838989217
Book Description
By finelybook
Get a head start in the world of AI and deep learning by: developing your skills with PyTorch
Want to get to grips with one of the most popular machine learning libraries for deep learning? The Deep Learning with PyTorch Workshop will help you do just that,jumpstarting your knowledge of using PyTorch for deep learning even if you’re starting from scratch.
It’s no surprise that deep learning’s popularity has risen steeply in the past few years,thanks to intelligent applications such as self-driving vehicles,chatbots,and voice-activated assistants that are making our lives easier. This book will take you inside the world of deep learning,where you’ll use PyTorch to understand the complexity of neural network architectures.
The Deep Learning with PyTorch Workshop starts with an introduction to deep learning and its applications. You’ll explore the syntax of PyTorch and learn how to define a network architecture and train a model. Next,you’ll learn about three main neural network architectures – convolutional,artificial,and recurrent – and even solve real-world data problems using these networks. Later chapters will show you how to create a style transfer model to develop a new image from two images,before finally taking you through how RNNs store memory to solve key data issues.
By the end of this book,you’ll have mastered the essential concepts,tools,and libraries of PyTorch to develop your own deep neural networks and intelligent apps.
What you will learn
Explore the different applications of deep learning
Understand the PyTorch approach to building neural networks
Create and train your very own perceptron using PyTorch
Solve regression problems using artificial neural networks (ANNs)
Handle computer vision problems with convolutional neural networks (CNNs)
Perform language translation tasks using recurrent neural networks (RNNs)
