Do you want to empower your business to make smarter and faster decisions using insights from data? Just hiring a bunch of data scientists and letting them create fancy predictive models is rarely enough. Eventually, their creations need to be used in a production environment to make the endeavor worthwhile. With deployment techniques, data scientists can integrate the value of advanced analytics into your business applications through an API. This makes the models available for custom web apps or dashboards, which provide a human-friendly interface for your employees or customers.
In this course, you will learn how to build a simple web server with Python and Flask, which exposes a REST API, from which a client application can request predictions from a machine learning model. You will gain hands-on experience building a predictive model using scikit-learn, then exposing it as a service via an API in Docker. You will also learn to convert predictions to JSON format, which can be used by diverse clients such as browser-based dashboards.