Recently, I have completed the biostatistics M.S. thesis under the instructions of Dr. Hakmook Kang. The thesis work is mainly focused on the modeling part, which is used to explain the model in the papar by Kang, Hakmook, et al. “A bayesian double fusion model for resting-state brain connectivity using joint functional and structural data.” Brain connectivity 7.4 (2017): 219-227. You can read the Readme, slides or code from GitHub. Also, I want to express thanks to the fantastic course (BIOS 8366: advanced statistical computing) taught by Dr. Fonnesbeck Christopher, which allows me to learn PyMC3 from scratch.

Here I wrote slides about preparations of data science interviews for people who are in need. You can check my slides which are previewd by RawGit.

In this early morning of Super Bowl Day, I finally finished Deep Learning Specialization taught by Andrew Ng.

Please see my github for details.

Before I started my biostatistics master at Vanderbilt University, I learned related probability knowledge pretty much in high school for mathematical contest. Luckily, it is very close to the interview problems like cards or coin-flip. However, starting to learn the fundamental concepts of probability and statistics is the key to analytics in data science field.