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You're reading from  Simplifying Data Engineering and Analytics with Delta

Product typeBook
Published inJul 2022
PublisherPackt
ISBN-139781801814867
Edition1st Edition
Concepts
Big Data
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Author (1)
Anindita Mahapatra
Anindita Mahapatra
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Anindita Mahapatra

Anindita Mahapatra is a Solutions Architect at Databricks in the data and AI space helping clients across all industry verticals reap value from their data infrastructure investments. She teaches a data engineering and analytics course at Harvard University as part of their extension school program. She has extensive big data and Hadoop consulting experience from Thinkbig/Teradata prior to which she was managing development of algorithmic app discovery and promotion for both Nokia and Microsoft AppStores. She holds a Masters degree in Liberal Arts and Management from Harvard Extension School, a Masters in Computer Science from Boston University and a Bachelors in Computer Science from BITS Pilani, India.
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Formalizing the ML development process

Let us first understand what constitutes a model and how we define MLOps. It is important to emphasize that this chapter is not about the nitty gritty details of creating a model, but rather about the data aspects of creating a good model and the process of continuously refining it to keep it relevant and useful to the business.

What is a model?

A model is an artifact that has several inputs and outputs. Let's list them so we have a firm idea of what a model encompasses. The following diagram captures our definition of an ML asset and its refinement zones:

Figure 9.7 – What is a model?

The inputs to this process include the following elements:

  • One or more datasets
  • One or more libraries used to create the model
  • The source code used to create the model with a given architecture
  • The distinct values for the various hyperparameters used to train the model
  • Additional metadata such as...
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Simplifying Data Engineering and Analytics with Delta
Published in: Jul 2022Publisher: PacktISBN-13: 9781801814867
© 2022 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Anindita Mahapatra

Anindita Mahapatra is a Solutions Architect at Databricks in the data and AI space helping clients across all industry verticals reap value from their data infrastructure investments. She teaches a data engineering and analytics course at Harvard University as part of their extension school program. She has extensive big data and Hadoop consulting experience from Thinkbig/Teradata prior to which she was managing development of algorithmic app discovery and promotion for both Nokia and Microsoft AppStores. She holds a Masters degree in Liberal Arts and Management from Harvard Extension School, a Masters in Computer Science from Boston University and a Bachelors in Computer Science from BITS Pilani, India.
Read more about Anindita Mahapatra

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