Joomi K

Data: Competition for drivendata.org
Techniques: Classification, random forest, PCA

Data: Wine sales data
Techniques: k-means clustering, recommender systems, matrix factorization

Data: Telecom customer data
Techniques: Calculating churn probability and expected loss, random forest

Data: Student test scores
Techniques: Bayesian analysis, hypothesis testing, MCMC

Data: Records of consumers selecting different candy brands.
Techniques: Feature selection, regression

Data: Income data from the UCI ML Repository
Techniques: Classification, random forest

Data: Monthly armed robberies
Techniques: ARIMA models, stationarity tests, differencing

Data: Time series of mining accidents
Techniques: Bayesian analysis, MCMC

Data: Boston housing dataset
Techniques: Gradient boosted regression trees

Data: Synthetic data
Techniques: MCMC

Data: RNASeq data
Techniques: Multiple comparison testing, PCA, clustering

Data: Twitter API
Techniques: NLP, logistic regression, latent Dirichlet allocation, scraping

Data: Twitter API
Techniques: NLP, sentiment analysis with various models, scraping

Data: Accident data in NYC
Techniques: Exploratory analysis