As a data scientist in an organization you frequently find yourself in a couple of situations: you have a dataset, you want to extract some useful… Read More »Not tools, focusing on problems: a project cycle in data science
Visualizing census data could not be easier thanks to few great packages in R. Not that in Python you could not do spatial analysis/visualization of… Read More »Making maps to visualize census data
Problem statement Price and quantity sold are the two determinants of business revenue/profit. At higher price the revenue is expected to be high. But this… Read More »Optimizing price, maximizing revenue
1. Background New home construction plays a significant role in housing economy, while simultaneously impacting other sectors such as timber, furniture and home appliances. New… Read More »New Home Sales Projection: A Time Series Forecasting
“The internet is killing retail. Bookstores are just the first to go.” — quoted in this NYT article. Retail bookstores are in a death row; looks… Read More »Predicting the demise of retail bookstores: a time series forecasting
I picked up a little book called “Finance Basics” published by Harvard Business Review Press, for a short in-flight reading. This tiny book isn’t going… Read More »Finance basics for data scientists
A time series is a sequence of data points recorded at specific time points – most often in regular time intervals (seconds, hours, days, months… Read More »Time-series data mining & applications
Developed at MIT’s Sloan School of Management in 1950s system dynamics is a methodological approach to model the behavior of complex systems, where change in… Read More »Data Science meets System Dynamics
In a previous blog I wrote about 6 potential applications of time series…. To recap, they are the following: Trend analysis Outlier/anomaly detection Examining shocks/unexpected… Read More »Outlier detection with time-series data mining
