This is a content-based movie recommendation system that uses text Vectorization method Bag of Words (BoW) Term Frequency, and some advanced Python libraries like Nltk, Numpy, pandas, and streamlit for a better User Interface.
What is a content-based Recommendation System(RM)? In RM, the algorithms search for similarities such as genre, directors, descriptions, actors, etc. before recommending something. The idea is that if a person enjoyed one movie or show, he/she might like one similarly.
What is Bag of Words (BoW) Term Frequency? The bag-of-words model is commonly used in methods of document classification in which the occurrence of each word is used as a feature for training a classifier.
Install required libraries.
pip install streamlit
pip install numpy
pip install pandas
pip install pickle
pip install nltk
A content-based movie recommendation system that uses text Vectorization method Bag of Words (BoW) Term Frequency, and some advanced Python libraries like Nltk, Numpy, pandas, and streamlit for a better User Interface.