Time Series Analysis using ARIMA

ARIMA is a family of models used to analyze and characterize time series/temporal data. Although rudimentary compared to more modern methods, ARIMA is comparably simpler and an easier introduction to time series analysis.

Matrix Factorization using Alternating Least Squares (ALS)

One method of dimension reduction is that of matrix factorization. Just as the name implies, a matrix is 'factored' so that the resulting factors approximate the original matrix when multiplied together.

Portfolio Analysis with Statistics

While there are many methods of optimizing a stock portfolio, one such method is to maximize its excess return to volatility ratio. Such a model aims to find a middle ground between profitability and stability.

Online Bayesian Regression

Online updates for Bayesian regression allow it to scale better with data dimension as well as reduces the amount of running memory required for loading data or data streams.