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You're reading from  Machine Learning Engineering with MLflow

Product typeBook
Published inAug 2021
PublisherPackt
ISBN-139781800560796
Edition1st Edition
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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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Getting started with the experiments module

To get started with the technical modules, you will need to get started with the environment prepared for this chapter in the following folder: https://github.com/PacktPublishing/Machine-Learning-Engineering-with-MLflow/tree/master/Chapter04

You should be able, at this stage, to execute the make command to build up your workbench with the dependencies needed to follow along with this chapter. You need next to type the following command to move to the right directory:

$ cd Chapter04/gradflow/

To start the environment, you need to run the following command:

$ make

The entry point to start managing experimentation in MLflow is the experiments interface illustrated in Figure 4.1:

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Figure 4.1 – The Experiments interface in MLflow

On the left pane (1), you can manage and create experiments, and on the right (2), you can query details of a specific...

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Machine Learning Engineering with MLflow
Published in: Aug 2021Publisher: PacktISBN-13: 9781800560796

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