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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.

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)

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

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Unfortunately, due to several restrictions, we are unable to ship to the following countries:

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hanyu Nov 15, 2020

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

Abdul Najeeb Jan 20, 2021

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.

Yalin Mar 29, 2021

I think it is the best book for beginners to learn PyTorch

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

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