Data
Science

Spring 2020
course
site

Friday the 13 of March

Some of your work.

Notice complexities of using scikit learn for this stuff : lots of buzzwords from probability and statistics that you need to wade through, lots of technical jargon in the API that you need to stare at to fit their (powerful, general, professional) tools to your particular problem.

Here are a few notebooks on kaggle using their sample dataset and MultinomialNB from scikit-learn :

And some of Paul Graham's articles on this topic :

After break

I'm not quite sure what we should spend our time on after break. We'll have about five weeks, and I'd like you to spend a good chunk of that time on your own projects.

Here are the machine learning ideas from the text

Definitions and summaries of these are at :

... already too much to do in the time remaining. Your thoughts?

https://cs.marlboro.college /cours /spring2020 /data /notes /mar13
last modified Tue October 15 2024 6:00 am