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Updated 2 years ago
Netflix Content Recommendation System
Recommendation Systems are the systems that predict and filter the future preferences of user based based on their past experience. They are widely to recommend
- similar products (Amazon, Flipkart)
- relevant media, e.g. photos, videos and stories (Instagram)
- relevant series and movies (Netflix, Amazon Prime Video, Hotstar)
- relevant songs and podcasts (Spotify)
- relevant videos (YouTube)
- similar users, posts (LinkedIn, Twitter, Instagram)
- relevant dishes and restaurants (Uber Eats, Zomato, Swiggy)
There are mainly 2 types of Recommendation System
- Content Based RS
- Collaborative Filtering
Content Based Recommendation Systems
There are cases when the user is new on a platform and we end up having no prior information on the user. In such scenerios, we recommend similar items based on comments, feedbacks, reviews, description of the items with which the user interacts.
Models/ Algorithms like TF-IDF score, word2vec are used to capture the similarty in Content Based RS.
Downloading the Dataset
!pip install jovian opendatasets --upgrade --quiet
Let's begin by downloading the data, and listing the files within the dataset.