style: clean 3. readme

3-Web-App/README.md

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 # Build a web app to use your ML model
 
-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. 
+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.
 
 ![UFO Parking](images/ufo.jpg)
 
 Photo by <a href="https://unsplash.com/@mdherren?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Michael Herren</a> on <a href="https://unsplash.com/s/photos/ufo?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a>
-
 
 ## Lessons
 
 1. [Build a Web App](1-Web-App/README.md)
 
 ## Credits
 
-"Build a Web App" was written with ♥️ by [Jen Looper](https://twitter.com/jenlooper). 
+"Build a Web App" was written with ♥️ by [Jen Looper](https://twitter.com/jenlooper).
 
 ♥️ The quizzes were written by Rohan Raj.
 
-The dataset is sourced from [Kaggle](https://www.kaggle.com/NUFORC/ufo-sightings). 
+The dataset is sourced from [Kaggle](https://www.kaggle.com/NUFORC/ufo-sightings).
 
-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.
+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.