Projects

Kaggle ML March Madness 2022

Data aggregation and feature engineering using dbt + BigQuery
NCAA 2022 Repo

Kaggle ML March Madness 2020

Sadly the tournament didn’t happned this year, so I’ll have to wait until next year to officially compete on Kaggle. On the training data provided by Kaggle, by including external data and summary season stats I was able to achieve log-loss in the .3-.5 range for each of the 2014-2019 seasons, and better accuracy than just always picking the higher ranked team. Some of the work that went into the project is below.

NCAA Tourney Dashboard (Tableau Public)
Used BeautifulSoup to get stats from TeamRankings.com and KenPom.com -Get External NCAA Basketball Stats
Python Code - NCAA Notebook
- Reformat data to list lower TeamID first, same format needed for Kaggle submission.
- Aggregate regular season stats to use as features.
- Add regular season, KenPom and TeamRanking stats to TourneyResults data to create data set for training and testing.
- Create features that compare each stat for team_x and team_y (difference and ratio).
- Define function for training and testing. For example, train on the 2007-2014 tournaments, test on 2015 tournament.

Fairfax County Property Values & Prices

Looking through data.gov, I saw quite a bit of data provided by Fairfax County tax administration office. The data consisted of assessed values for the land and buildings for each parcel, including residential and commercial, so I filtered just for those residential parcels with only 1 building on it to try to get an equivalent to single-family homes. I was originally looking for home prices similar to what might be on RedFin or Zillow, but since they had made so much data available it seemed a shame not to use it.

Median Assessed Property Values viz (Tableau Public)
Exploratory analysis using Streamlit and plotly. Streamlit gif
The data is available via API.
- Calling data.gov API Python.
Access data using the API, aggregate, cleanse, visualize, and ultimately explore the relationship between house size and number of bedrooms and bathrooms with their sale price and appraised value for each city in Fairfax County. R Script

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