From Science to Implementation

During my summer internship, I closely observed how scientific models are combined with real-time data to generate tailored information for each farm to guide daily agricultural operations. I realize one big difference between the data science in industry settings and the work that we do in academics, is how this company’s science does not stop at the point when the model was proved to be working.

My 2018 in data

It is the time of the year when you look back at the promises that you have been trying to keep but failed. An honest review of the year 2018 using data collected via Fitbit, web browsing time via Chrome, and self-logged time.

Readable R code

In my previous post, I talked about managing projects with Github and how crucial it is to make your work reproducible. While we craft our writings on paper to present the idea better, it is equally important to make our code readable for someone trying to understand the work.

Project Management with RStudio and Github

This post is inspired by Professor Mallory’s presentation on Reproducible Research Practices for Economists. See the presentation version that I gave at a lab meeting. Summary Introduced project management practices for file management and version controls.

Writing Plan July 2018

I spent the last week on a road trip and had many thoughts on what to write during those long driving hours. I decided to start with a writing plan.

Planning a lot

The number one reason for procrastinating is perhaps the task at hand is too hard to accomplish, and the mind would prefer more manageable tasks. Instead of writing up your result from the last set of regressions or editing the paper draft for one more time, your brain is easily satisfied at checking emails or grading homework.

Work 4 productive hours a day

I came across this article Daily Routine of a 4 Hour Programmer recently and was impressed by how the author manages to work only four hours a day and remain productive.