Our background, Our Passions, Our Blog.....

Welcome to the blog of two not-so-socially awkward physicists: Jason Schissel (theorist) and Brian Choi (experimentalist). We ran into each other during graduate school in the department of physics at UCLA. As it happens, we both gravitated towards algorithm development, predictive modeling, and machine learning. What we realized is that we wanted to share our experiences and ideas with the data science community to proliferate the use of machine learning and statistical methods in solving real-world problems, finding elegant solutions to seemingly complex systems, and optimizing predictions while stressing the importance of interpreting and deeply understanding the results.

The purpose of this blog is simple: introduce concepts and ideas which we (and anyone else in the data science community) find interesting. The concepts will center around our passions in statistics, probability, machine learning, and linear algebra. There will be toy data sets, actual data sets, and visualization aids to drive concepts beyond simple understanding, hopefully reaching your intuition. Finally, and practically, we will codify the concepts and ideas into scripting or programming languages such as: MATLAB, Python, and C++.

As the blog title states, this blog will follow a format of posts which will: THINK, MODEL, then CODE the chosen topics to a point where the reader can learn, practice, and execute these methods on their own data.

We hope you enjoy reading our blog, learn a few things!