AchintaMitra23 / Movie-Recommendation-System-Using-Sentiment-Analysis Public

Notifications You must be signed in to change notification settings
Fork 0
Star 0

System is going to filter out the best possible movies basis on some criteria in recommendation area even after analyzing and previewing the reviews of the particular movie using sentiment analysis theory.

0 stars 0 forks Branches Tags Activity

Notifications

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
.ipynb_checkpoints		.ipynb_checkpoints
Collaborative Filtering.ipynb		Collaborative Filtering.ipynb
Content Based Filtering.ipynb		Content Based Filtering.ipynb
NLP pipeline.ipynb		NLP pipeline.ipynb
README.md		README.md
Sentiment Analysis On Movies using MNB.ipynb		Sentiment Analysis On Movies using MNB.ipynb
Sentiment Analysis.ipynb		Sentiment Analysis.ipynb

Repository files navigation

Movie-Recommendation-System-Using-Sentiment-Analysis

Used CSV files from Kaggle (Links are given below) : IMDB Dataset : https://www.kaggle.com/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews. TMDB_5000_credits : https://www.kaggle.com/tmdb/tmdb-movie-metadata?select=tmdb_5000_credits.csv. TMDB_5000_movies : https://www.kaggle.com/tmdb/tmdb-movie-metadata?select=tmdb_5000_movies.csv. Movie : https://www.kaggle.com/grouplens/movielens-20m-dataset?select=movie.csv. Rating : https://www.kaggle.com/grouplens/movielens-20m-dataset?select=rating.csv

About

System is going to filter out the best possible movies basis on some criteria in recommendation area even after analyzing and previewing the reviews of the particular movie using sentiment analysis theory.

python nlp machine-learning naive-bayes-classifier cosine-similarity count-vectorizer knn-classification pearson-correlation collaborativefiltering tfidf-vectorizer contentbasedfiltering

Report repository

Releases

No releases published

Packages

No packages published

Languages

Jupyter Notebook 100.0%