tanyaschlusser / office-nfl-pool
A fun introduction to Pandas andScikit-Learn using nfl data
☆45Updated 9 years ago
Alternatives and similar repositories for office-nfl-pool:
Users that are interested in office-nfl-pool are comparing it to the libraries listed below
- Materials for my PyData Seattle talk☆21Updated 9 years ago
- Using data to dig into the 2015 NL Cy Young race☆10Updated 9 years ago
- Portland Python Meetup March 2015☆40Updated 10 years ago
- Scripts to Analyze Pronto's Data Release☆24Updated 9 years ago
- Ranking NFL teams☆48Updated 12 years ago
- ☆34Updated 8 years ago
- ☆69Updated 9 years ago
- PyData NYC 2015 conference☆94Updated 9 years ago
- Material for some talks I have given☆62Updated 6 months ago
- Repository for exploratory data transformation & visualization talk☆27Updated 8 years ago
- ☆52Updated 8 years ago
- PyData Madrid 2016 material for the talk: A Primer to recommendation Systems☆37Updated 9 years ago
- Machine Learning with Scikit-Learn (material for pydata Amsterdam 2016)☆30Updated 9 years ago
- ☆16Updated 6 years ago
- Notebook version of an article on the Fast Forward Labs blog☆61Updated 7 years ago
- repository for code related to the end-to-end data analysis in python workshop, from the Open Data Science Conference 2015☆15Updated 9 years ago
- Contains my ipython notebooks and data on the NBA☆22Updated 9 years ago
- ☆41Updated 9 years ago
- Common post-estimation tasks for scikit-learn☆17Updated 8 years ago
- Fantasy Football Analysis☆24Updated 11 years ago
- (Deprecated) Task for the Search & Discovery data analyst job.☆21Updated 9 years ago
- Machine Learning the NFL Draft☆19Updated 8 years ago
- Materials for my pandas tutorial at PyData 2014, NYC☆111Updated 9 years ago
- Articles on Data Science, Jupyter, and Pandas☆18Updated 9 years ago
- My talk at Strata 2014 in Santa Clara, CA☆73Updated 11 years ago
- ☆29Updated 8 years ago
- ☆84Updated 7 years ago
- 12 Week Data Science Immersive☆27Updated 9 years ago
- FiveThirtyEight replica☆17Updated 9 years ago
- For the pandas tutorial at PyData Seattle: https://www.youtube.com/watch?v=otCriSKVV_8☆116Updated 3 years ago