Nathan Cheever - Understanding Data

Jekyll2022-07-20T09:20:08-05:00https://cheevahagadog.github.io/blog/feed.xmlNathan Cheever - Understanding DataData Science BlogFastpages Notebook Blog Post2020-02-20T00:00:00-06:002020-02-20T00:00:00-06:00https://cheevahagadog.github.io/blog/jupyter/2020/02/20/test

Doing Data Analytics at AdvancedMD2019-06-13T00:00:00-05:002019-06-13T00:00:00-05:00https://cheevahagadog.github.io/blog/python/r/sql/interview/2019/06/13/data-sci-amds

(Note: This was originally written by me and published on UtahDataScientist.com)

No more looping for me! Vectorizing in Pandas and Other Fun Tricks2018-07-09T00:00:00-05:002018-07-09T00:00:00-05:00https://cheevahagadog.github.io/blog/python/pandas/2018/07/09/vectorizing-pandas

Pandas is awesome. I use it nearly everyday for my work and side projects because it makes working with data so easy.

Finding out which features contributed to each row’s prediction2018-03-17T00:00:00-05:002018-03-17T00:00:00-05:00https://cheevahagadog.github.io/blog/machine%20learning/2018/03/17/model-explanations

Almost completed with a machine learning project, I was asked by the client if I could include what the reasons where for each prediction. I had done feature importances before, but never was I asked to (or thought of) listing out what the reasons where behind each prediction made by my model.

How I made my own newsletter from my bookmarks with Python2017-10-15T00:00:00-05:002017-10-15T00:00:00-05:00https://cheevahagadog.github.io/blog/python/2017/10/15/barker-create-a-newsletter

I have a lot of bookmarks that I actively curate. I’m kinda a bookmark junkie, carefully considering where each one belongs. For example, here’s a picture of what my visualization folder looks like: