from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
import numpy as np
 
# Creating dummy data
X = np.array([[0], [1], [2], [3], [4], [5]])
y = np.array([0, 1, 2, 3, 4, 5])
 
# Creating a simple neural network model
model = Sequential([
    Dense(10, input_dim=1, activation='relu'),
    Dense(1)  # Output layer
])
 
# Compiling the model
model.compile(optimizer='adam', loss='mean_squared_error')
 
# Training the model
model.fit(X, y, epochs=50, verbose=0)
 
# Making a prediction
print("Prediction for input 6:", model.predict(np.array([[6]])))
 

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