title: ANN problem: I am building an ANN model to predict the profit of a new startup based on certain features
body: <p><a href="https://i.stack.imgur.com/WpVsG.png" rel="nofollow noreferrer">The image of the dataset</a></p>
  <pre><code>import numpy as np
  from keras.models import Sequential
  from keras.layers import Dense
  </code></pre>
  <h1>Loading the data set using pandas as data frame format</h1>
  <pre><code>import pandas as pd
  df = pd.read_csv(r&quot;E:\50_Startups.csv&quot;)
  df.drop(['State'],axis = 1, inplace = True)
  
  from sklearn.preprocessing import MinMaxScaler
  mm = MinMaxScaler()
  df.iloc[:,:] = mm.fit_transform(df.iloc[:,:])
  info = df.describe()
  
  x = df.iloc[:,:-1].values
  y = df.iloc[:,-1].values
  
  from sklearn.model_selection import train_test_split
  x_train,x_test,y_train,y_test = train_test_split( x,y, test_size=0.2, random_state=42)
  </code></pre>
  <h1>Initializing the model</h1>
  <pre><code>model = Sequential()
  model.add(Dense(40,input_dim =3,activation=&quot;relu&quot;,kernel_initializer='he_normal'))
  model.add(Dense(30,activation=&quot;relu&quot;))
  model.add(Dense(1))
  model.compile(loss=&quot;mean_squared_error&quot;,optimizer=&quot;adam&quot;,metrics=[&quot;accuracy&quot;])
  </code></pre>
  <h1>fitting model on train data</h1>
  <pre><code>model.fit(x=x_train,y=y_train,epochs=150, batch_size=32,verbose=1)
  </code></pre>
  <h1>Evaluating the model on test data</h1>
  <pre><code>eval_score_test = model.evaluate(x_test,y_test,verbose = 1)
  </code></pre>
  <p>I am getting zero accuracy.</p>