Vim-wielding Pythonista with an interest in Machine Learning
Who am I?
I am a work-a-holic who happens to be a perfectionist. Needless to say I enjoy making things, lots and lots of things :)
If I find free time (outside of school, work and side projects), you can find me reading Hacker News or watching one of the (too many) tv shows I still happen to keep up with.
Recently, I have dedicated some time to learning a bit about the (massive) field of Machine Learning. I've taken a few MOOC's in my spare time that covered some fundamental ML theory. I've also tried my hand at working to solve some basic problems using machine learning techniques. I worked with some classification algorithms to perform realtime sentiment analysis on tweets during the 2016 election. I've also written a neural net which would (attempt to) procedurally generate music after having been trained on a relatively small set of open domain classical songs.
Another hobby I have is building mobile applications. In my opinion, there is
nothing more rewarding than watching the impact that one of my
creations can have on the lives of others. Developing
applications for mobile devices is unique in the fact that your
creation can be used by millions of users, as well as yourself, in a very easy and convenient way. Instant gratification.
No servers (usually) and no upfront costs!
What have I done?
I have practical experience in several
different languages, including but not limited to: Java (and
Python is my love affair. If I need to solve a problem, I usually reach for my terminal and start up a Python prompt. I've worked with Python at Wish where I was a payment's engineer, dealing with high volume payments (on the order of hundreds of millions of dollars bi-weekly). I've used Python for several side projects. I also completed 3 Coursera courses (perks of being an employee) which involved using Python to solve a variety of problems with machine learning techniques. I've used numpy, scipy and scikit-learn (as well as some Graphlab create). I've played around with tensorflow. I've also played around with some simple neural nets as well as some genetic algorithms. I can easily say that Python is my favorite problem solving tool.
Now comes C++. Being an engineer, C++ is a very natural choice for most projects. In most cases, most of my school courses have used C++ at one point or another.
As a result, I now have a portfolio of C++ projects which range from sorting algorithms, to a compiler, even my own compression algorithm.
I am a self taught iOS programmer (took Stanford iOS Application Development course) with professional experience as well (XE.com now Euronet). I have delved into large Objective C code bases, though I have also (luckily or unluckily)
had experience to all Swift versions, all the way from 1 to 3. MacOS has been an exploratory platform for me. On one hand, its nice making apps that you can use immediately that look nice on your computer, though the lack of being able to run these experiements cross platform have forced me to resist getting in too deep.
I have quite a bit of experience with Android and Java in general. In fact, I first learned to program by creating Android applications. I have developed a plethora of applications for the Android platform (albeit some extremely basic) and have launched 4 full featured applications on the Google Play Store. I also was one of the developers for Coursera's Android application. If you open up the Coursera application, and you see that timeline on your homepage, that was me. Also, the whole audio streaming architecture allowing for background audio was one of the projects I undertook. To top it all off, I made relatively large contributions to the content processing system that renders all quizzes and exams on the phone (render html code and math expressions).
I have always loved to hack around with new things so it
won't come as a surprise to you when you find out that the
projects I have worked on range from a variety of different
platforms, languages and frameworks. I worked
with wearables (including the Pebble smartwatch, Myo
armband, as well as both Android Wear watches and the Apple Watch), and with more mainstream devices such as Android
devices, iPhones, Android TV's and much much more.