Reader small image

You're reading from  The Deep Learning Architect's Handbook

Product typeBook
Published inDec 2023
PublisherPackt
ISBN-139781803243795
Edition1st Edition
Right arrow
Author (1)
Ee Kin Chin
Ee Kin Chin
author image
Ee Kin Chin

Ee Kin Chin is a Senior Deep Learning Engineer at DataRobot. He holds a Bachelor of Engineering (Honours) in Electronics with a major in Telecommunications. Ee Kin is an expert in the field of Deep Learning, Data Science, Machine Learning, Artificial Intelligence, Supervised Learning, Unsupervised Learning, Python, Keras, Pytorch, and related technologies. He has a proven track record of delivering successful projects in these areas and is dedicated to staying up to date with the latest advancements in the field.
Read more about Ee Kin Chin

Right arrow

Identifying key DL model deployment requirements

To determine the most suitable deployment strategy from a variety of options, it is essential to identify and define seven key requirements. These are latency and availability, cost, scalability, model hardware, data privacy, safety, and trust and reliability requirements. Let’s dive into each of these requirements in detail:

  • Latency and availability requirements: These are two closely connected components and should be defined together. Availability requirements refer to the desired level of uptime and accessibility of the model’s prediction. Latency requirements refer to the maximum acceptable delay or response time that the models must meet to provide timely predictions or results. A deployment with a low availability requirement usually can tolerate high latency predictions, and vice versa. One reason is that a low-latency capable infrastructure can’t ensure low latency if it is not available when model...
lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
The Deep Learning Architect's Handbook
Published in: Dec 2023Publisher: PacktISBN-13: 9781803243795

Author (1)

author image
Ee Kin Chin

Ee Kin Chin is a Senior Deep Learning Engineer at DataRobot. He holds a Bachelor of Engineering (Honours) in Electronics with a major in Telecommunications. Ee Kin is an expert in the field of Deep Learning, Data Science, Machine Learning, Artificial Intelligence, Supervised Learning, Unsupervised Learning, Python, Keras, Pytorch, and related technologies. He has a proven track record of delivering successful projects in these areas and is dedicated to staying up to date with the latest advancements in the field.
Read more about Ee Kin Chin