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auto_encoder_train movie lens
 
from keras.models import Sequential
from keras.models import Model
from keras.layers import Input , Dense , Dropout
from sklearn.model_selection import train_test_split
from keras.models import load_model
import numpy as np
import pandas as pd
 
def fun(num):
    if( num < 3 ):
        return 0
    else:
        return 1
 
 
#taking input 
 
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
new= ratings.drop(['timestamp'] , axis =1 )
 
final_ratings = new.pivot(index='userId' , columns='movieId' , values='rating')
 
final_ratings = final_ratings.fillna(0) 
 
final_ratings = final_ratings.applymap( fun )
 
x_train, x_test = train_test_split(final_ratings , train_size=0.8)
 
 
input_img = Input(shape=(9724,))
 
 
encoded = Dense(units=512, activation='relu')(input_img)
encoded = Dense(256, activation='relu')(encoded)
#encoded = Dense(64, activation='relu')(encoded)
encoded = Dropout(0.5)(encoded)
 
decoded = Dense(256, activation='relu')(encoded)
decoded = Dense(512, activation='relu')(decoded)
decoded = Dense(9724, activation='sigmoid')(decoded)
 
 
autoencoder = Model(input_img, decoded)
 
encoder = Model(input_img, encoded)
 
#compile 
 
autoencoder.compile( optimizer='adam' , loss = 'binary_crossentropy' , metrics=['accuracy'] )
 
autoencoder.fit( x_train , x_train , epochs=30, batch_size=300 , shuffle = True )
 
autoencoder.save('autoencoder.h5')

Main.java:1: error: class, interface, or enum expected
auto_encoder_train movie lens
^
Main.java:3: error: '.' expected
from keras.models import Sequential
                                   ^
Main.java:4: error: ';' expected
from keras.models import Model
    ^
Main.java:4: error: '.' expected
from keras.models import Model
                              ^
Main.java:5: error: ';' expected
from keras.layers import Input , Dense , Dropout
    ^
Main.java:5: error: '.' expected
from keras.layers import Input , Dense , Dropout
                              ^
Main.java:5: error: ';' expected
from keras.layers import Input , Dense , Dropout
                                ^
Main.java:5: error: class, interface, or enum expected
from keras.layers import Input , Dense , Dropout
                                       ^
Main.java:5: error: class, interface, or enum expected
from keras.layers import Input , Dense , Dropout
                                         ^
Main.java:6: error: '.' expected
from sklearn.model_selection import train_test_split
                                                    ^
Main.java:7: error: ';' expected
from keras.models import load_model
    ^
Main.java:7: error: '.' expected
from keras.models import load_model
                                   ^
Main.java:8: error: ';' expected
import numpy as np
      ^
Main.java:8: error: class, interface, or enum expected
import numpy as np
             ^
Main.java:9: error: '.' expected
import pandas as pd
             ^
Main.java:9: error: ';' expected
import pandas as pd
                ^
Main.java:18: error: illegal character: '#'
#taking input 
^
Main.java:20: error: unclosed character literal
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                       ^
Main.java:20: error: illegal character: '\'
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                          ^
Main.java:20: error: illegal character: '\'
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                           ^
Main.java:20: error: illegal character: '\'
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                                 ^
Main.java:20: error: illegal character: '\'
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                                         ^
Main.java:20: error: illegal character: '\'
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                                          ^
Main.java:20: error: illegal character: '\'
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                                                    ^
Main.java:20: error: illegal character: '\'
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                                                     ^
Main.java:20: error: illegal character: '\'
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                                                                     ^
Main.java:20: error: illegal character: '\'
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                                                                      ^
Main.java:20: error: illegal character: '\'
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                                                                                      ^
Main.java:20: error: illegal character: '\'
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                                                                                       ^
Main.java:20: error: unclosed character literal
ratings = pd.read_csv( 'C:\\Users\sahil.1\\Downloads\\ml-latest-small\\ml-latest-small\\ratings.csv' )
                                                                                                   ^
Main.java:21: error: unclosed character literal
new= ratings.drop(['timestamp'] , axis =1 )
                   ^
Main.java:21: error: unclosed character literal
new= ratings.drop(['timestamp'] , axis =1 )
                             ^
Main.java:23: error: unclosed character literal
final_ratings = new.pivot(index='userId' , columns='movieId' , values='rating')
                                ^
Main.java:23: error: unclosed character literal
final_ratings = new.pivot(index='userId' , columns='movieId' , values='rating')
                                       ^
Main.java:23: error: unclosed character literal
final_ratings = new.pivot(index='userId' , columns='movieId' , values='rating')
                                                   ^
Main.java:23: error: unclosed character literal
final_ratings = new.pivot(index='userId' , columns='movieId' , values='rating')
                                                           ^
Main.java:23: error: unclosed character literal
final_ratings = new.pivot(index='userId' , columns='movieId' , values='rating')
                                                                      ^
Main.java:23: error: unclosed character literal
final_ratings = new.pivot(index='userId' , columns='movieId' , values='rating')
                                                                             ^
Main.java:35: error: unclosed character literal
encoded = Dense(units=512, activation='relu')(input_img)
                                      ^
Main.java:35: error: unclosed character literal
encoded = Dense(units=512, activation='relu')(input_img)
                                           ^
Main.java:36: error: unclosed character literal
encoded = Dense(256, activation='relu')(encoded)
                                ^
Main.java:36: error: unclosed character literal
encoded = Dense(256, activation='relu')(encoded)
                                     ^
Main.java:37: error: illegal character: '#'
#encoded = Dense(64, activation='relu')(encoded)
^
Main.java:37: error: unclosed character literal
#encoded = Dense(64, activation='relu')(encoded)
                                ^
Main.java:37: error: unclosed character literal
#encoded = Dense(64, activation='relu')(encoded)
                                     ^
Main.java:40: error: unclosed character literal
decoded = Dense(256, activation='relu')(encoded)
                                ^
Main.java:40: error: unclosed character literal
decoded = Dense(256, activation='relu')(encoded)
                                     ^
Main.java:41: error: unclosed character literal
decoded = Dense(512, activation='relu')(decoded)
                                ^
Main.java:41: error: unclosed character literal
decoded = Dense(512, activation='relu')(decoded)
                                     ^
Main.java:42: error: unclosed character literal
decoded = Dense(9724, activation='sigmoid')(decoded)
                                 ^
Main.java:42: error: unclosed character literal
decoded = Dense(9724, activation='sigmoid')(decoded)
                                         ^
Main.java:49: error: illegal character: '#'
#compile 
^
Main.java:51: error: unclosed character literal
autoencoder.compile( optimizer='adam' , loss = 'binary_crossentropy' , metrics=['accuracy'] )
                               ^
Main.java:51: error: unclosed character literal
autoencoder.compile( optimizer='adam' , loss = 'binary_crossentropy' , metrics=['accuracy'] )
                                    ^
Main.java:51: error: unclosed character literal
autoencoder.compile( optimizer='adam' , loss = 'binary_crossentropy' , metrics=['accuracy'] )
                                               ^
Main.java:51: error: unclosed character literal
autoencoder.compile( optimizer='adam' , loss = 'binary_crossentropy' , metrics=['accuracy'] )
                                                                   ^
Main.java:51: error: unclosed character literal
autoencoder.compile( optimizer='adam' , loss = 'binary_crossentropy' , metrics=['accuracy'] )
                                                                                ^
Main.java:51: error: unclosed character literal
autoencoder.compile( optimizer='adam' , loss = 'binary_crossentropy' , metrics=['accuracy'] )
                                                                                         ^
Main.java:55: error: unclosed character literal
autoencoder.save('autoencoder.h5')
                 ^
Main.java:55: error: unclosed character literal
autoencoder.save('autoencoder.h5')
                                ^
60 errors

Standard output is empty