Introduction to Models as Web Endpoints
Explore how to deploy predictive machine learning models as web endpoints to provide real-time results. Learn to host and consume models using Python, save them for production, and scale services with tools like Gunicorn and Heroku. Understand how to build interactive applications with Plotly Dash and integrate models into broader data pipelines.
Predictive model as a web endpoint
In order for a machine learning model to be useful, you need a way of sharing the results with other services and applications within your organization. While you can precompute results and save them to a database using a batch pipeline approach, it’s often necessary to respond to requests in real-time with up-to-date information. One way of achieving this goal is by ...