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Building a Movie Recommendation Engine in Python using Scikit-Learn

#artificialintelligence

Wondered how Google comes up with movies that are similar to the ones you like? After reading this post you will be able to build one such recommendation system for yourself. Now you might be thinking "That's interesting. But, what are the differences between these recommendation engines?". Let me help you out with that.


Movies Recommendation System (Content-based)

#artificialintelligence

The aim of this project is to recommend the movies to the user based on their favorite movies. Like, whenever a user searches for any movie so this system recommends movies that are of the same type. So, let's look up the code!! The shape of this dataset is (4803,24). After this, I selected some relevant features that are essential.


How to find the best music, movie, and TV recommendations

Popular Science

Apple Music uses a similar system, but with hearts instead of thumbs up. You can also go to Account and then Choose Artists For You: Here, you tell the service about the singers and bands you love. As for Spotify, check out the Discover Weekly and My Daily Mix playlists it automatically generates for you. If you hear any music that particularly grabs you, save it to your personal library to improve the recommendations even further. Similar options will be available whatever your app or service of choice.


Deep Learning Meets Recommendation Systems

@machinelearnbot

Almost everyone loves to spend their leisure time to watch movies with their family and friends. We all have the same experience when we sit on our couch to choose a movie that we are going to watch and spend the next two hours but can't even find one after 20 minutes. We definitely need a computer agent to provide movie recommendation to us when we need to choose a movie and save our time. Apparently, a movie recommendation agent has already become an essential part of our life.. According to Data Science Central "Although hard data is difficult to come by, many informed sources estimate that, for the major ecommerce platforms like Amazon and Netflix, that recommenders may be responsible for as much as 10% to 25% of incremental revenue."


Deep Learning Meets Recommendation Systems

@machinelearnbot

Almost everyone loves to spend their leisure time to watch movies with their family and friends. We all have the same experience when we sit on our couch to choose a movie that we are going to watch and spend the next two hours but can't even find one after 20 minutes. We definitely need a computer agent to provide movie recommendation to us when we need to choose a movie and save our time. Apparently, a movie recommendation agent has already become an essential part of our life.. According to Data Science Central "Although hard data is difficult to come by, many informed sources estimate that, for the major ecommerce platforms like Amazon and Netflix, that recommenders may be responsible for as much as 10% to 25% of incremental revenue."