Movie Recommendation System

A recommender system or a recommendation system (sometimes replacing “system” with a synonym such as platform or engine) is a subclass of information filtering system that seeks to predict the “rating” or “preference” a user would give to an item

and putting in a simple language “a recommendation system suggest anything relevant based on the used interest”

Installation

Use the Package manager pip to install various dependencies .

pip install pandas 
pip numpy as np
pip seaborn as sns
pip install scipy 
pip install ast
pip install sklearn
pip install nltk
pip install surprise

Importing Dependencies

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from scipy import stats
from ast import literal_eval
from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
from sklearn.metrics.pairwise import linear_kernel, cosine_similarity
from nltk.stem.snowball import SnowballStemmer
from nltk.stem.wordnet import WordNetLemmatizer
from nltk.corpus import wordnet
from surprise import Reader, Dataset, SVD, evaluate

Content Based Filtering


The idea behind Content-based (cognitive filtering) recommendation system is to recommend an item based on a comparison between the content of the items and a user profile.In simple words,I may get recommendation for a movie based on the description of other movies.

Team

• Naman Mittal

• Neerav Jain

• Niti Mangwani