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You're reading from  Machine Learning Engineering with MLflow

Product typeBook
Published inAug 2021
PublisherPackt
ISBN-139781800560796
Edition1st Edition
Tools
Maven
Concepts
Machine Learning
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Author (1)
Natu Lauchande
Natu Lauchande
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Natu Lauchande

Natu Lauchande is a principal data engineer in the fintech space currently tackling problems at the intersection of machine learning, data engineering, and distributed systems. He has worked in diverse industries, including biomedical/pharma research, cloud, fintech, and e-commerce/mobile. Along the way, he had the opportunity to be granted a patent (as co-inventor) in distributed systems, publish in a top academic journal, and contribute to open source software. He has also been very active as a speaker at machine learning/tech conferences and meetups.
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Developing models with a Databricks Community Edition environment

In many scenarios of small teams and companies, starting up a centralized ML environment might be a costly, resource-intensive, upfront investment. A team being able to quickly scale and getting a team up to speed is critical to unlocking the value of ML in an organization. The use of managed services is very relevant in these cases to start prototyping systems and to begin to understand the viability of using ML at a lower cost.

A very popular managed ML and data platform is the Databricks platform, developed by the same company that developed MLflow. We will use in this section the Databricks Community Edition version and license targeted for students and personal use.

In order to explore the Databricks platform to develop and share models, you need to execute the following steps:

  1. Sign up to Databricks Community Edition at https://community.cloud.databricks.com/ and create an account.
  2. Log in to your...
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Machine Learning Engineering with MLflow
Published in: Aug 2021Publisher: PacktISBN-13: 9781800560796
© 2021 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Natu Lauchande

Natu Lauchande is a principal data engineer in the fintech space currently tackling problems at the intersection of machine learning, data engineering, and distributed systems. He has worked in diverse industries, including biomedical/pharma research, cloud, fintech, and e-commerce/mobile. Along the way, he had the opportunity to be granted a patent (as co-inventor) in distributed systems, publish in a top academic journal, and contribute to open source software. He has also been very active as a speaker at machine learning/tech conferences and meetups.
Read more about Natu Lauchande

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