How Does a Recommendation Engine Work | Netflix Recommendation System | Machine Learning | #shorts

How many times have you finished a Netflix series and you got recommended a new one in a similar genre? Do you know how do streaming platforms do it? Watch this fun snippet to find out.

Watch the full episode here: https://youtu.be/TqRq-tMyQwA

What is a recommendation engine?
A recommendation engine is a software system that analyses user behaviour and data to provide personalised suggestions for items or content. It uses algorithms and machine learning techniques to understand user preferences and make predictions about what they are likely to be interested in. These suggestions can be anything from products, services, or content such as movies, music, or articles. Recommendation engines are commonly used by businesses to improve customer engagement, increase sales, and improve user experience by making it easier for users to find what they are looking for.

What platforms use a recommendation system?
Recommendation systems are used on a wide range of platforms across various industries. Some of the most common platforms that use recommendation systems include:

1. E-commerce websites such as Amazon, Alibaba, and eBay, which use recommendation systems to suggest products to customers based on their browsing and purchase history.

2. Streaming services such as Netflix, Spotify, and YouTube, which use recommendation systems to suggest movies, TV shows, songs, and videos based on users' viewing and listening history.

3. Social media platforms such as Facebook and Instagram, which use recommendation systems to suggest content and pages to users based on their interests and activity on the platform.

4. News and content websites such as Medium and The New York Times, which use recommendation systems to suggest articles and content based on users' reading history.

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