A Movie Recommendation System in Python from Scratch

Author(s): Serafeim Loukas, PhD

Originally published on Towards AI.

In this article, I explain simply how to build a movie recommendation system in Python!
Image made by the author using DALL-E diffusion model.

After a short break from writing, we are back! Today we will speak about a very exciting topic: Recommendation Systems.

Does the sentence “Since you liked/watched X, you might also like Y” ring a bell?

Well, it surely does!

A huge majority of people use on a daily basis services and websites like Amazon, YouTube, and Netflix. These services are excellent in suggesting recommendations based on the user’s preferences. For example, Netflix can accurately suggest interesting movies based on the user’s movie-watching history and liking. Amazon, is also excellent in recommending new items to the client according to the history of item purchasing or browsing (items watched/bought in the past). Finally, YouTube does the same job by recommending new videos that a watcher might like according to historical information and preferences (e.g. views, likes, etc).

Recommendation systems are tools and methods aiming at suggesting relevant items to users. As explained in the previous paragraph, they are widely used in various industries, such as retail, entertainment, and online services, to personalize the user experience by suggesting products, services, media content, and more.

There are many types/families of recommendation systems but here we we only speak about the 2… Read the full blog for free on Medium.

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Published via Towards AI