DATA SCIENCE IN YOUR DAILY LIFE: There’s a data scientist behind those movie recommendations!

Blogs > DATA SCIENCE IN YOUR DAILY LIFE: There’s a data scientist behind those movie recommendations!

THERE’S A DATA SCIENTIST BEHIND THOSE MOVIE RECOMMENDATIONS!
Do you remember the last time you watched a Netflix crime thriller movie like “The Departed”, and in turn, received recommendations for other amazing movies such as “The Godfather” or “Gone Baby Gone”? Welcome to the world of data science and Machine Learning!

In the 21st Century postmodern world, every nook and cranny of the world is in the process of becoming connected through virtual reality. CDs, DVD players and even cable television are now being considered “worn out” and “old technology” in order to pave way for more upcoming and happening ones such as Netflix, Prime and YouTube. However, what’s even more upcoming is that this technology seems to understand our unique preferences, and moreover, also suggest other relevant TV shows and web series based on one’s viewing habits. The same applies to online shopping as well – it may have happened scores of times that Amazon suggested other cool Apple products based on your previous iPhone 6 purchase.
The question that now arises is how these websites can be so omniscient as to recognize multiple unique viewing and purchasing habits so efficiently and accurately, an also crawl the database for other similar items and present it to the respective Internet users.

We’re back with a blog, and today, let’s venture into the upcoming and exciting world of data science, which has been popularly termed by Turing Award winner Jim Gray as “the sexiest job of the 21st Century”. Let’s have a sneak peek into the world where data scientists are busy with their numerous algorithms that allow machines to independently carry out these prediction tasks with ease:

1. So what’s so scientific in data science?
While science and technology have ensured that machines and technical equipment make our lives unbelievably efficient and quicker every single day, there is still a severe direct dependence of technological equipment on humans if the traditional sources of science and technology be relied upon alone. It is also important to ensure that technology work by itself for a major part of its functioning, instead of depending on constant human intervention. Moreover, with the inception of modern-day software and myriad online platforms to ensure that the world is well-connected, there is a massive explosion of data produced every single day. Just as it is essential to ensure less clutter and more clarity in our external worlds, the online world also needs to be maintained and de-cluttered on a regular basis. And in order to ensure that the technology of Machine Learning and organization of data may be incorporated to software systems, it is important to move one step beyond traditional science and technology, and embrace the world of ‘data science’.
Data scientists perform a world of algorithms – incorporating scientific techniques and systems in order to organize and store massive amounts of online information. If the internet world is a cobweb of information, data scientists are the spiders – venturing through the silk-threads efficiently.

2.Whoa! So how does a data scientist perform that herculean task?
The job of a data scientist is seeped into statistics and algorithms. Data scientists apply predictive modeling, machine learning and inferential statistics in the course of their work. Applying these different tools and techniques, a data scientist then traces certain unique patterns that are characteristic of specific internet users; and systematically stores this information in the database.
However, the task of a data scientist does not end here. A data scientist also uses the technology of Machine Learning, and allows your software to become independent enough to implement these algorithms effectively, so that the machines do not have to depend on humans every time such predictions need to be carried out.
And that, my friends, is the mystery behind all those Amazon and Netflix recommendations that you receive when you’re on an online shopping spree, or when you binge-watch your favourite web series on that lazy weekend!

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