Hello!

Today:

1. Right now: Download ML.zip, put in class notes, extract
2. Right now: Read README.md in that folder
3. Next few slides > take vocab notes in readme

Today:

• Essential vocab
• The "lego pieces" we can assemble to make ML magic
• A quick taste of the cracker barrel sized menu of ML option

Not like this:

Like this:

Ok, open the readme, you can take notes there.

A quick tour of sklearn, via the "Getting Started" page

• "estimator", "fit", "predict"
• "pipeline":
  • still fit and predict, but also:
  • handles preprocessing, feature creation and reduction, then estimating... without mechanical data leaks
• "cross_validate": CV + pipelines = algo scores you can trust

Prof demo: ML template

Now... let's work in ML Worksheet 1.ipynb