You're reading from Hands-On Python Deep Learning for the Web

Product typeBook

Published inMay 2020

Reading LevelBeginner

PublisherPackt

ISBN-139781789956085

Edition1st Edition

Languages

Python

Tools

Django TensorFlow

Concepts

Deep Learning

Authors (2):

Anubhav Singh

Sayak Paul

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Popular tools for deploying ML in production

In this section, we will be discussing some popular tools used for putting ML in production systems. The core utility provided by these tools is automating the learning-prediction-feedback pipeline and facilitating the monitoring of the model's quality and performance. While it is very much possible to create your own tools for this, it is highly recommended that you use any of the following tools, as per the requirements of your software.

Let's begin by discussing creme.

creme

creme is a Python library that allows us to perform online learning efficiently. Before we look at creme in action, let's have a brief discussion about online learning itself:

In online learning...

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Hands-On Python Deep Learning for the Web

Published in: May 2020Publisher: PacktISBN-13: 9781789956085

Authors (2)

Anubhav Singh

Anubhav Singh, a web developer since before Bootstrap was launched, is an explorer of technologies, often pulling off crazy combinations of uncommon tech. An international rank holder in the Cyber Olympiad, he started off by developing his own social network and search engine as his first projects at the age of 15, which stood among the top 500 websites of India during their operational years. He's continuously developing software for the community in domains with roads less walked on. You can often catch him guiding students on how to approach ML or the web, or both together. He's also the founder of The Code Foundation, an AI-focused start-up. Anubhav is a Venkat Panchapakesan Memorial Scholarship awardee and an Intel Software Innovator.
Read more about Anubhav Singh

Sayak Paul

Sayak Paul is currently with PyImageSearch, where he applies deep learning to solve real-world problems in computer vision and bring solutions to edge devices. He is responsible for providing Q&A support to PyImageSearch readers. His areas of interest include computer vision, generative modeling, and more. Previously at DataCamp, Sayak developed projects and practice pools. Prior to DataCamp, Sayak worked at TCS Research and Innovation (TRDDC) on data privacy. There, he was a part of TCS's critically acclaimed GDPR solution called Crystal Ball. Outside of work, Sayak loves to write technical articles and speak at developer meetups and conferences.
Read more about Sayak Paul

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