Applied Data Science — Manufacturing — Part I of V

In-line data has enormous predictive power of the quality of a product. For January, we'll be looking at measurement of parts as they move through a manufacturing line. The data set contains ~ 1 million entries
with ~ 3,000 numerical and categorical variables and a pass/fail annotation from quality control.

Participants will work together in small groups, brainstorming ideas and
building models to predict whether parts would PASS/FAIL quality control.

Everyone from beginners to experts is welcome. As always, our three
objectives are:

1. Provide skill-level-appropriate challenges to all participants.

2. Participants work with and learn from one another.

3. Those who attend all five Sundays finish a project they can add to their github/resume/portfolio.

Bring your favorite data analysis software! We're language-agnostic.

If you don't already have a favorite analysis tool, here are a few
suggestions: http://goo.gl/W8Q6cV