Today, I’m writing about a Data Science project I recently completed, in one of my favorite fields, Applied Finance. I used Data Science to calculate and compare profitability and risk of different investments using the Sharpe Ratio. Sharpe Ratio compares the expected returns for two investment opportunities and calculates the additional return per unit of risk an investor could obtain by choosing one over the other.

In this project, we'll compare the stock investment data for two tech firms- Facebook and Amazon using Data Science, and use S&P 500 as the benchmark to find out which one is a better choice to buy. The factors taken into consideration are- returns as well as the risk taken by the investor.

In this video tutorial, we'll explore World Bank's International Debt Statistics with the help of PostgreSQL.

Commercial banks receive a lot of applications for credit cards. Many of them get rejected for many reasons, like high loan balances, low-income levels, or too many inquiries on an individual's credit report, for example. Manually analyzing these applications is mundane, error-prone, and time-consuming (and time is money!). Luckily, this task can be automated with the power of machine learning, and pretty much every commercial bank does so nowadays. In this notebook, I've built an automatic credit card approval predictor using machine learning techniques, just like the real banks do.

If I were to describe the whole experience in one word, honestly, I won’t be able to. However, ‘supercalifragilisticexpialidocious’ can be a word. Don’t get in a flap if you don’t know that one (I too came across it just a week back!). Setting the context, I won the Women In Open Source Award 2019 by Red Hat. I was invited to Red Hat Summit in Boston, Massachusetts to accept the award on stage. Also, to shoot my introductory video that was to be shown on stage during my award ceremony, Tom had visited me in India along with a movie director and a crew of cameramen, a month back.

Two weeks back, I visited the city of Barcelona with a friend, Amit for the much-awaited Linux App Summit. It was organized by GNOME Foundation and KDE Community together. I was excited to be on the organizing team for the summit. It was my first experience being on the organizers’ side and not attendees' side, for such a large-scale event, and it was a really great experience.

Hola! I hope you all are safe in this pandemic, and are able to adjust to this new normal that is just surfacing. Today, I want to take a few minutes to talk about the ‘Right to be Forgotten’. As Wikipedia defines, “it reflects the claim of an individual to have certain data deleted so that third persons can no longer trace them.” Did you just catch yourself thinking that it doesn't matter much to me, because hey, who am I hiding from? Who’s gonna put efforts in tracing me, lol?