Hi, I'm Dinko!
If you like what you see here and want to chat, let's connect on LinkedIn 😄
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- Implemented an end-to-end scalable search engine for Wikipedia articles with MapReduce
- Developed a RESTful API to rank results of user queries with PageRank and tf-idf analysis
- Created a user interface with tunable weights
Tools: MapReduce, Flask, Jinja
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- Demonstrated difference in distribution of 3 point field goal percentage for seeded versus non-seeded teams in March Madness
- Justified use of permutational t-test with power analysis through Monte Carlo Simulations
- Published Medium article demonstrating effective and clear communication of advanced statistical concepts
Tools: dplyr, ggplot2
- College Football Game Prediction | Python, SQL
- Goal: Collect data manually from the API at collegefootballdata.com ✔️
- Goal: Predict winner of a college football game given season average statistics, talent, and returning production ✔️
- Goal: Deploy model, allowing users to select any 2 teams since 2015 to predict winner of hypothetical matchup
Tools: Web Scraping, Pandas, Scikit-Learn
These machine learning projects are on the docket and I'm very excited to share them upon completion
- Customer Churn | R
- Goal: Predict if a bank customer will turnover on their credit card services given card type; marriage, income, and education status, etc.
Tools: dplyr, ggplot2, tidymodels
- Spotify Popularity | Python
- Goal: Predict how popular a song will become on Spotify given characteristics such as danceability, energy, key, etc.
Tools: Pandas, Scikit-learn