Recently Kaggle master Kazanova along with some of his friends released a "How to win a data science competition" Coursera course. The Course involved a final project which itself was a time series prediction problem. Here I will describe how I got a top 10 position as of writing this…

I have been looking to create this list for a while now. There are many people on quora who ask me how I started in the data science field. And so I wanted to create this reference.

To be frank, when I first started learning it all looked very utopian and out of the world. The Andrew Ng course felt like black magic. And it still doesn't cease to amaze me. After all, we are predicting the future. Take the case of Nate Silver - What else can you call his success if not Black…

A data scientist needs to be Critical and always on a lookout for something that misses others. So here is some advice that one can include in the day to day data science work to be better at their work:

1. Beware of the Clean Data Syndrome

You need to ask yourself questions even before you start working on the data. **Does this data make sense?** Falsely assuming that the data is clean could lead you towards wrong Hypotheses. Apart from that, you can discern a…