Top MLOps Tools Data Scientists must know in 2022

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Introduction

Machine Learning Operations, or MLOps for short, is the process of putting machine learning models into production, and maintaining and monitoring them on a continuous basis is the core objective of MLOps. MLOps is a team sport combining skills and expertise from data scientists, data engineers, machine learning engineers, and DevOps engineers. The primary benefits of MLOps are efficiency, scalability, and reproducibility.

MLOps includes everything from the data flow to the deployment of machine learning models. In some situations, MLOps implementation is just used for model deployment, but you can also find more mature enterprises that have implemented MLOps across a variety of ML Lifecycle development domains, such as exploratory data analysis (EDA), data preprocessing, model training, etc.

Image Source: Databricks

MLflow

MLflow is an open source platform for managing the end-to-end machine learning lifecycle. It has the following primary components:

• Tracking: Allows you to track experiments to record and compare parameters and results.
• Models: Allow you to manage…