BDA-602 - Machine Learning Engineering

Dr. Julien Pierret

Lecture 13

In Summary

• HTTP is what we want to use to interface with our model
  • GET requests
• We want our service to be RESTful
• flask is what we'll use to wrap our models into a service
• pickle is what you'll use to serialize your models
  • Could also use dill
• CURL used to test service via the command line
• Postman good if you want a GUI application
• ngrok good for testing the service

No "official" Homework

• Start on your final project
  • Start building features (predictors) on your dataset
    • This is what I really want you to focus on
    • Build a ton of features based off your data
    • Imagination!!
  • Start analyzing those features with the tools with built in class
    • How do they perform?
    • Can you combine them with other features?
    • Are they correlated with other ones?
      • Is one better than the other? Why?