In this liveProject, you’ll deploy a machine learning model to production so it can be easily used by colleagues. You’ll create a virtual environment for deploying your application, use Flask to build a local web service that returns predictions, and Heroku for remote deployment.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
This liveProject is for intermediate Python data scientists who want to expand their capabilities in effective production deployment. To begin this liveProject you will need to be familiar with:
- Basics of Pandas
- Basics of NumPy
- Basics of Joblib/Pickle
- Basics of Flask
- Jupyter Notebooks
you will learn
In this liveProject, you’ll make a proven-and-tested machine learning model easily available in production to non-technical users.
- Creation and maintenance of a virtual environment
- GET and POST requests
- Creating a web framework for your weather prediction application
- Saving and loading of sklearn objects
- Remote deployment on Heroku