Posts on this blog are usually a result of my graduate school assignments and work. When I have time I do projects for recreation and report here. Sometimes I take online courses from Coursera and share my work on this blog when sharing is appropriate.
Some posts have links to
.Rmd files. I am a huge proponent of reproducible research and provide code where applicable. Every post can be saved as a
Ubuntu 16.04 alongside Windows 7/8/10 for Data Science
beginner #python #jupyter #linux #windows #r #data-science #git #anaconda
Having a Lenovo Y500 laptop with good specs (8GB RAM, 4 processors) that runs on Windows 7 made me feel limited when it came to scientific computing. Unix based systems like Linux and Mac OS are more convenient to use than Windows systems. As a result, after doing some research I decided to install a Linux distribution Ubuntu 16.04 aka Xenial alongside my Widnows 7 OS. This gives me the option to boot any of the two. I heavily use Python 2.7, 3.5 and R which I all install on my new Ubuntu partition. Below are the steps that worked for me. Hopefully, you find them useful.
Visualizing Indego bike geoson data in Python using Folium
beginner #python #ipynb #geoson #indego-bike-share #philly
Linear optimization and baseball teams
intermediate #r #opr #linear-optimization #integer #datatable #rmarkdown
We try to use Integer Linear Programming to build a perfect 25 men roster baseball team. We present our best team below which is the solution of the ILP model we built using the 2015 MLB season player data. If you understand baseball please evaluate our resulting baseball team and drop a comment, so that we know whether ILP can be used to get a decent baseball team. After the table I describe how we arrived at our solution.
Impact of weather events in the US
intermediate #r #coursera #reproducible #datatable #rickshaw #rpubs #rmarkdown
Using the U.S. National Oceanic and Atmospheric Administration’s (NOAA) storm database I explore which weather events are most harmful to population health and economy in the US.
In undergrad I wrote a tutorial on #Julia programming language in which I analyzed the output of the Collatz function. The Collatz Conjecture was really fascinating to me due to its seemingly simple wording and almost impossible to solve mystery. Since then, #Julia changed significantly, and Terence Tao made a contribution that gets us closer to the proof of the Collatz Conjecture.