AlmaBetter Verfied Project - AlmaBetter School
This dataset consists of tv shows and movies available on Netflix as of 2019. The dataset is collected from Flixable which is a third-party Netflix search engine. In 2018, they released an interesting report which shows that the number of TV shows on Netflix has nearly tripled since 2010. The streaming service’s number of movies has decreased by more than 2,000 titles since 2010, while its number of TV shows has nearly tripled. It will be interesting to explore what all other insights can be obtained from the same dataset. We will be using clustering algorithm to find out interesting patterns for different sets of data grouped together in clusters.
The recommendation systems are an integral part of many streaming services like Netflix, and Amazon Prime. Here in this project, we have tried to find similar movies based on content or textual features. This can be used in a content-based recommendation system where when a user searches for a particular category, similar movies get populated. Also, various inferences are drawn which can help to understand what kind of content is more popular in various countries. Clustering helps businesses to convert the large available dataset into meaningful structures.
Sakshi Dhyani | Avid Learner | Data Scientist | Machine Learning Engineer | Deep Learning enthusiast
