Kaggle, the place to be for data scientists

Kaggle is quite a new platform but actually pretty cool if you love data and data science.

The purpose of Kaggle is to gather a community of data scientists around data analysis and prospective analysis. Firms can launch competition between analysts from all around the global who will jump in, trying to solve forecasting issues. The inscription to the website is free and quite easy to do, you can also do a Facebook connect or a Google connect. Easy then, registration doesn’t take more than 1 minute.

Kaggle is also a good platform to learn how to get into Data science, learning by doing. Honestly, when it comes to programming, the best school is the “Do it Yourself” school, meaning putting your hands dirty, trying, breaking, repeating until it works. You’ll learn data science and programming languages such as R or Python applied to data science thanks to all the scripts available, shared freely with the users. This will be the opportunity to discover libraries on Python such as Pandas, numpy or apply dataset concepts.

Rewards are being set up by companies who really want to get their problem solved. Data science is sometimes better with money… So a top notch can earn a couple of box from it, which is cool given the time some users spend trying to figure out a way to better forecast sales activity for instance. Also, let’s be honest, most of the users don’t do it for the money but more the “pretige” and the intellectual challenge this kind of project represents.

It’s also the occasion to be discovered and maybe get some job proposals as a data scientist. Data scientists can actually leverage this platform to get visibility among the community of users and be contacted for a contract. The “Data scientist” job is amongst the most demanded in the Valley: many companies have a hell incredible amount of data but lack of skills to leverage it and improve their product / customer experience based on these very data.

Have you been on Kaggle? What’s your insight on it? Would you spend some time on it ?

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