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The Deep Learning with PyTorch Workshop
The Deep Learning with PyTorch Workshop

The Deep Learning with PyTorch Workshop: Build deep neural networks and artificial intelligence applications with PyTorch

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Key benefits

  • Learn how to define your own network architecture in deep learning
  • Implement helpful methods to create and train a model using PyTorch syntax
  • Discover how intelligent applications using features like image recognition and speech recognition really process your data

Description

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.

Who is this book for?

This deep learning book is ideal for anyone who wants to create and train deep learning models using PyTorch. A solid understanding of the Python programming language and its packages will help you grasp the topics covered in the book more quickly.

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)

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 22, 2020
Length: 330 pages
Edition : 1st
Language : English
ISBN-13 : 9781838981846
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What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
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Product Details

Publication date : Jul 22, 2020
Length: 330 pages
Edition : 1st
Language : English
ISBN-13 : 9781838981846
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Total $ 121.97
The Deep Learning with PyTorch Workshop
$38.99
The Deep Learning Workshop
$43.99
The Deep Learning with Keras Workshop
$38.99
Total $ 121.97 Stars icon
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Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(3 Ratings)
5 star 100%
4 star 0%
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Yalin Mar 29, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I think it is the best book for beginners to learn PyTorch
Amazon Verified review Amazon
Abdul Najeeb Jan 20, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book is well written, i.e. very readable, explaining what is going on very well. As a tool for learning about Deep Learning with PyTorch, it is good. The coverage of topics is plenty from being able to talk precisely about common things like data processing to more advanced stuff like error analysis or model deployment.One of my favorite features about this book was the code examples that teach you to step by step with the help of screenshots on how to try out the example for yourself.This is a book for someone who wants to know the basics of deep learning with PyTorch and wants to get a thorough understanding of what they can achieve with PyTorch.
Amazon Verified review Amazon
hanyu Nov 15, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
An awesome and comprehensive introduction textbook of deep learning for beginner and intermediate readers. It has captured tremendous amount of information regarding to building a deep learning model based application, which included data processing (missing value, outlier, imbalanced data etc.), model training, error analysis to model deployment. Besides the high-level math foundation behind the model, the author provides step-by-step code examples and output screenshots for readers to follow and build their application. Also, it’s clear and well written to make readers have a wide understanding of multiple deep learning models such as CNN, RNN by using Pytorch. I recommend this book to person who is new to deep learning area and wants to learn from building practical applications before taking a deep dive into too complicated algorithms and concept.
Amazon Verified review Amazon
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