BioScope-Recommendation-API

• Blog Link : https://towardsdatascience.com/build-a-movie-recommendation-api-using-scikit-learn-flask-and-heroku-bee239dc96e3

• API Link : https://bioscope-api.herokuapp.com/movie?title=insert-movie-name

An open movie recommendation API that has been built using Python and deployed on Heroku. This API is based on the Content-Based Filtering technique used in recommendation systems where we recommend items to a user based on the input item's attributes. We have more than 6000 movies present in our dataset and our recommendation algorithm works accordingly.

Use the BioScope API whilst building your website or app and recommend movies to your users accordingly.

Source Datasets:-

• TMDB 5000 Movies Dataset: https://www.kaggle.com/tmdb/tmdb-movie-metadata
• The Indian Movie Database: https://www.kaggle.com/tmdb/tmdb-movie-metadata

File Description:-

recommendation.py

Here, we have our logic written for the recommendation algorithm. Consists a total of 5 functions

get_data():-

• get_data() is used to fetch the data about the movies and return the dataset with it's attributes as the result for further preprocessing.

combine_data():-

• combine_data() drops the columns not required for feature extraction and then combines the cast and genres column,finally returning the combine column as the result of this function.

transform_data():-

• transform_data() takes the value returned by combine_data() and the plot column from get_data() and applies CountVectorizer and TfidfVectorizer respectively and calculates the Cosine values.

recommend_movies():-

• recommend_movies() takes four parameters i.e movie_name and return values of get_data(), combine_data(), transform_data as input and returns the top 20 movies similar to our input movie.

results():-

• result() takes a movie's title as input and returns the top 20 recommendations using the recommend_movies() function.

app.py

• The Flask app where we use the recommendation.py as a module and return the results in JSON format.

requirements.txt

• This has all the dependencies required to deploy our application on Heroku

Procfile

• A Procfile is a file which describes how to run your application.

Folder

Dataset

• Contains the dataset we have used to build our recommendation system.