Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications

Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications
Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications
By 作者: Ian Pointer
ISBN-10 书号: 1492045357
ISBN-13 书号: 9781492045359
Edition 版本: 1
Release Finelybook 出版日期: 2019-10-08
pages 页数: (220 )

$49.99

Book Description to Finelybook sorting

Take the next steps toward mastering deep learning, the machine learning method that’s transforming the world around us by the second. In this practical book, you’ll get up to speed on key ideas using Facebook’s open source PyTorch framework and gain the latest skills you need to create your very own neural networks.
Ian Pointer shows you how to set up PyTorch on a cloud-based environment, then walks you through the creation of neural architectures that facilitate operations on images, sound, text,and more through deep dives into each element. He also covers the critical concepts of applying transfer learning to images, debugging models, and PyTorch in production.

Learn how to deploy deep learning models to production
Explore PyTorch use cases from several leading companies
Learn how to apply transfer learning to images
Apply cutting-edge NLP techniques using a model trained on Wikipedia
Use PyTorch’s torchaudio library to classify audio data with a convolutional-based model
Debug PyTorch models using TensorBoard and flame graphs
Deploy PyTorch applications in production in Docker containers and Kubernetes clusters running on Google Cloud
Preface
1.Time Series:An Overview and a Quick History
2.Finding and Wrangling Time Series Data
3.Exploratory Data Analysis for Time Series
4.Simulating Time Series Data
5.Storing Temporal Data
6.Statistical Models for Time Series
7.State Space Models for Time Series
8.Generating and Selecting Features for a Time Series
9.Machine Learning for Time Series
10.Deep Learning for Time Series
11.Measuring Error
12.Performance Considerations in Fitting and Serving Time Series Models
13.Healthcare Applications
14.Financial Applications
15.Time Series for Government
16.Time Series Packages
17.Forecasts About Forecasting
Index

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