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”
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
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
![](C:\Users\Nirav\Desktop\ml stanford\highly elastic demand curve - Google Search_files\cbf.png)
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.
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Naman Mittal
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Neerav Jain
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Niti Mangwani