Movie Recommendation System

Inspiration

My teammate Ved and I are movie lovers and we think that one of the issues that movie loving people face is trying to find the perfect movie for them. Because of this they tend to spend hours searching reviews and what not, hence we both decided to tackle this problem by making a recommender system which would recommend you a movie based on what you have loved before.

What it does

So what our Machine Learning project does is that it takes an input from the user, it can be a keyword, genre or even an entire movie name which the user's has previously seen (and enjoyed) and the algorithm works and finds movies that matches their preference.

How we built it

We used Jupyter to create our machine learning model and streamlit (Python) to make the web application for the same

Challenges we ran into

We didn't really face any major issues while creating the machine learning model since Ved and I are both a little accustomed to it however we did run into some challenges while using streamlit

Accomplishments that we're proud of

Bringing our model to the web! This was our first time trying streamlit and running machine learning models on the web so we're really proud for that.

What we learned

How to use streamlit and bring machine learning models to the web.

What's next for Movie Recommendation System

Well right now the model works on our localhost, we would definitely want the model to be accessible on the global network so the next step would obviously be to deploy it on the net :)

Built With

• api
• dataset
• machine-learning
• python