Chapter 1: Introducing MLflow
MLflow is an open source platform for the machine learning (ML) life cycle, with a focus on reproducibility, training, and deployment. It is based on an open interface design and is able to work with any language or platform, with clients in Python and Java, and is accessible through a REST API. Scalability is also an important benefit that an ML developer can leverage with MLflow.
In this chapter of the book, we will take a look at how MLflow works, with the help of examples and sample code. This will build the necessary foundation for the rest of the book in order to use the concept to engineer an end-to-end ML project.
Specifically, we will look at the following sections in this chapter:
- What is MLflow?
- Getting started with MLflow
- Exploring MLflow modules
