Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách keo gáy, Bìa mềm
Thể loại:Computers
Năm:2020
Ngôn ngữ:english
Trang:330 / 329
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 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)
Who this book is 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.
Table of Contents
Introduction to Deep Learning and PyTorch
Building Blocks of Neural Networks
A Classification Problem Using DNNs
Convolutional Neural Networks
Style Transfer
Analyzing the Sequence of Data with RNNs
