In this section of the curriculum, you will be introduced to an applied ML topic: how to save your Scikit-learn model as a file that can be used to make predictions within a web application. Once the model is saved, you'll learn how to use it in a web app built in Flask. You'll first create a model using some data that's all about UFO sightings! Then, you'll build a web app that will allow you to input a number of seconds with a latitude and a longitude value to predict which country reported seeing a UFO.
Photo by <ahref="https://unsplash.com/@mdherren?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Michael Herren</a> on <ahref="https://unsplash.com/s/photos/ufo?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a>
The web app architecture was suggested in part by [this article](https://towardsdatascience.com/how-to-easily-deploy-machine-learning-models-using-flask-b95af8fe34d4) and [this repo](https://github.com/abhinavsagar/machine-learning-deployment) by Abhinav Sagar.
