Netflix machine learning

Remember the times when we were eagerly waiting for our favorite TV shows to air? Missing an episode was heartbreaking, and there wasn't any other way to watch it again. But now, thanks to the flexibility online media streaming services provide, you don't have to worry about missing any of the episodes. 

So which show are you currently watching? Right now, I'm watching Money Heist on Netflix, and it's a really good show. 

Speaking of Netflix, have you guys ever wondered how Netflix works? Well, today we're going to talk about the science behind Netflix. Netflix is considered to be one of the biggest internet television networks, with 158 million paying subscribers across the globe. 

Starting off in 1997, it allowed people to rent DVDs online. In 2007, it came out with its own streaming services. Customers could watch shows and movies on their computers, TV screens, phones, or gaming devices. 

In 2013, it began competing directly with TV networks and cable for original content. As of 2019, Netflix is the world's largest online streaming service. But how did that happen? What does Netflix do that its competitors don't? 

Well, the answer is machine learning, AI, and big data analytics. Netflix uses content delivery network to store and transmit their movies and TV shows. First, Netflix gets the content by negotiating licensing deals with TV shows and film makers. 

Depending on the location, popularity, and purchasing rights, Netflix displays different content for its users across the globe. That is why what you watch in the US is different from what you watch in Nigeria. But do you know there are also a few shows and movies which are common to all the users irrespective of their locations, like Netflix Originals, House of Cards, hit TV shows, and new releases? Netflix has over 7,000 movies and shows, and it is nearly impossible for us to find what we'd like to watch. 

So how does Netflix recommend these shows? To do this job, Netflix uses its recommendation engine. Imagine if you were new to Netflix. In the beginning, you would have to take up this survey and pick up the genres you are interested in. But after that, Netflix fine-tunes its recommendations to provide you with a more personalized experience, which means my recommendation list will be different from yours. 

What is machine learning? Machine learning is necessary for this job because it uses your previous data to make informed suggestions. Data such as what you have watched previously, your ratings, search history, and so on. All this complex data is analyzed, and finally, a conclusion is drawn. 

In addition to these personalized engines, what else catches your attention? Well, it is the thumbnails. Visually appealing thumbnails grab our attention, and there's something that we click on, isn't it? Yes, Netflix doesn't usually use the show's original cover art. It uses algorithms to extract high-quality images from the respective videos. 

With the help of aesthetic visual analysis and creativity, Netflix comes up with eye-catching thumbnails. 

So, this was all about the science behind Netflix. I hope you guys enjoyed this post. Please be kind enough to share it. Also, follow our blog by hitting the follow button below the comment box. Thank you for reading and stay tuned for more from Blueguard.

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