You're reading from Mastering PyTorch

Product typeBook

Published inFeb 2021

Reading LevelIntermediate

PublisherPackt

ISBN-139781789614381

Edition1st Edition

Languages

Python

Tools

PyTorch

Concepts

Deep Learning

Author (1)

Ashish Ranjan Jha

Serving PyTorch models in the cloud

Deep learning is computationally expensive and therefore demands powerful and sophisticated computational hardware. Not everyone might have access to a local machine that has enough CPUs and GPUs to train gigantic deep learning models in a reasonable time. Furthermore, we cannot guarantee 100 percent availability for a local machine that is serving a trained model for inference. For reasons such as these, cloud computing platforms are a vital alternative for both training and serving deep learning models.

In this section, we will discuss how to use PyTorch with some of the most popular cloud platforms – AWS, Google Cloud, and Microsoft Azure. We will explore the different ways of serving a trained PyTorch model in each of these platforms. The model-serving exercises we discussed in the earlier sections of this chapter were executed on a local machine. The goal of this section is to enable you to perform similar exercises using virtual machines...

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Mastering PyTorch

Published in: Feb 2021Publisher: PacktISBN-13: 9781789614381

Author (1)

Ashish Ranjan Jha

Ashish Ranjan Jha received his bachelor's degree in electrical engineering from IIT Roorkee (India), a master's degree in Computer Science from EPFL (Switzerland), and an MBA degree from Quantic School of Business (Washington). He has received a distinction in all 3 of his degrees. He has worked for large technology companies, including Oracle and Sony as well as the more recent tech unicorns such as Revolut, mostly focused on artificial intelligence. He currently works as a machine learning engineer. Ashish has worked on a range of products and projects, from developing an app that uses sensor data to predict the mode of transport to detecting fraud in car damage insurance claims. Besides being an author, machine learning engineer, and data scientist, he also blogs frequently on his personal blog site about the latest research and engineering topics around machine learning.
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Serving PyTorch models in the cloud

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Author (1)

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