Machine Learning Lifecycle: What it is, Challenges & Best Practices

Building a machine learning model is an iterative process. For a successful deployment, most of the steps are repeated several times to achieve optimal results. The model must be maintained after deployment and adapted to changing environment. Let's look at the details of the lifecycle of a machine learning model. The machine learning lifecycle is the process of developing, deploying, and managing a machine learning model for a specific application.