Overview of DSI-9 major projects:

• Hybrid Music Recommendation Engine (Capstone Project)

  • Sourcing own data (211 hours of audio, 25K tracks, 17K album reviews, 151K user artist follows) to build music recommender
  • Concepts: NLP (Topic Modeling/LDA), Audio Engineering (via Librosa), Recommenders (Collaborative-Filtering, Content-Based), Scraping (BS4, Selenium), Data Merging (Fuzzy Matching, Imputation Strategies), Neural Network Optimization

• Ames Housing Price Prediction

  • Using a variety of modeling technique to minimize RMSE for Ames, IA house prices as part of internal Kaggle competition
  • Concepts: Regression, Regularization, Gridsearching, Ensembling

• Reddit Humor Classification

  • Leveraging NLP techniques to classify whether or not a post is from r/Jokes v r/DadJokes
  • Programmatically building a validating 80+ models to find optimal combination of data, model, and hyperparameters
  • Concepts: Cvec/Tfidf Vectorization, Lemmatization/Stemming, Logistic Regression, Ensembling

• Disaster Relief Tool/Dash Concepting

  • Utitlizing FEMA data to deep dive into socioeconomic and disaster relief datasets
  • Construction of a corresponding Tableau dashboard to house model output and build prototype views for real life client
  • Concepts: Regression, Regularization, Tableau Visualization