30 Dec 2017
2017 was a long year, good nonetheless. I want to take a moment to look back at the highlights of 2017. Some of the things I cover here are the goals I set out at the beginning; some of my favorite books; the good stuff – research; and other miscellaneous things.
19 Dec 2017
If you had asked me why I want to go to university, and why I am studying what I am studying, a few months ago, I would have replied with superficial answers like, “Get a job” and “I love mathematics”. But after taking the class Critical Encounters, my answer is completely different. This class made me rethink several aspects of life, and question who I wanted to be.
30 Nov 2017
This article is a simplified version of the research report that aims at identifying and tracking craters in images for optical navigation in space. We first survey at existing image processing techniques. We then proceed to bootstrapping a deep neural network classifier with the help of TensorFlow Object Detection API and images from NASA’s Detecting Crater Impact Challenge. We then implement a preliminary tracking algorithm that stores images and computes mean squared error to detect if the crater has already been seen before.
12 Aug 2017
In the previous article, we used linear regression to predict the price of houses.
Then, we saw that this model does not find any non-linear correlations.
The most fascinating thing about neural networks is that they automatically model
any non-linearities present in the phenomenon.
In this article, we will use neural networks to overcome that shortcoming.
07 Aug 2017
3 days beside a beautiful lake, under the summer sun. 400 avid hackers who care about the community.
Thousands of ideas shared. That’s probably how I’d describe Hackcon V in three lines.
But it is so much more than that.
Hackcon is the annual conference that brings together some of the most passionate hackathon organizers
around the world to share ideas and views on how to make the hackathon community a better place for everyone.
31 Jul 2017
Linear regression is perhaps the heart of machine learning. At least where it all started.
And predicting the price of houses is the equivalent of the “Hello World” exercise in starting with linear regression.
This article gives an overview of applying linear regression techniques (and neural networks) to predict house prices using the Ames housing dataset.
15 Jul 2017
August is fast approaching. This means that summer is about to end and school is about to begin soon. For some of you, school might have already started.
And it’s time to start studying and managing stress again.
Learning tough concepts, remembering when assignments are due, juggling time between school and life, pulling in an all-nighter to finish that project, and what not. In short, it’s time to become more productive.