Movie Recommender System

Glimpse of the hollywood dataset

Inspiration

The pandemic has let many of us with lots of free time. And most of us have turned to theatre and movies for the sake of time pass. But to this solution also, we face another problem....Which movie to watch from this huge variety?? Will it suit my interest?

What it does

The project aims to recommend the movies to the user based upon their interest. It recommends based on various factors.

How we built it

The data was collected from kaggle and then analysis was performed on it. The web app was built by using machine learning algorithms in the backend to predict the movies which resemble to the selected movie. I chose genres, summary, actor names as the main attributes to decide which movie is the closest and similar to the chosen one.

Challenges we ran into

One of the major challenge, was to predict accurately as there was a huge dataset and I needed to filter out the most relevant attributes that would give us the correct result. Another challenge was to integrate the model with a web app. So, I handled it by using flack to my rescue.

Accomplishments that we're proud of

To make such a huge app all by alone is the major accomplishment I have acheived. Also, this app is production ready and so the common people can also use this.

What we learned

I learned Count Vectorization in ML and how to deploy ml models using flask.

What's next for Movie Recommender System

I would like to deploy this app on any platform like Heroku and would help all to get out of their movie selection dilemma. Also apart from hollywood and bollywood, I would like to bring other theatres in my dataset.