import streamlit as st import pickle import pandas as pd
st.title("Movie Recommender System") movie_dict=pickle.load(open('movie_dict','rb')) movie=pd.DataFrame(movie_dict) list=movie["title"].values similarity=pickle.load(open('similarity','rb'))
def recommend(movie1): y=0 for i in movie["title"].values: if (i==movie1): break else : y+=1 distance=similarity l=sorted(enumerate(distance[y]),reverse=True,key=(lambda x:x[1])) n=0 recomend=[] for i in l: if(n<5): recomend.append(movie["title"][i[0]]) n+=1 else : break return recomend
option = st.selectbox( "Enter MobileNo", list) if (st.button("prediction")): recomend=recommend(option) for i in recomend: print(i)