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The Deep Learning with PyTorch Workshop - Build deep neural networks and artificial intelligence applications with PyTorch (Paperback, 2 Ed)
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The Deep Learning with PyTorch Workshop - Build deep neural networks and artificial intelligence applications with PyTorch (Paperback, 2 Ed)
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Get a head start in the world of AI and deep learning by developing
your skills with PyTorch Key Features 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 Book DescriptionWant 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) Who this book is forThis 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.
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