Exercise: Train and Evaluate ML Model
Test the knowledge you've gained so far by applying it to this hands-on exercise.
We'll cover the following...
Now that we’ve reached the end of this chapter, its time for you to write some ML model code. We recommend following a more rigorous data science workflow this time, e.g., scikit-learn pipelines.
Problem statement
Write a script that would train and persist a model locally, as well as the train/test data used for it. Then upload your artifacts to Amazon S3 and write AWS Lambda code that will evaluate your model performance on train/test datasets. We have already ...