DEEP LEARNING NN MODULE

                                                 Build deep Learning NN models

LINK  : PROGRAM (DATASET - FETCH AUTOMATIC)

Aim

To build deep learning NN (Neural Network) models.

Algorithm

1.     Load the dataset

2.     Split the dataset into input x and output y

3.     Define the keras model

4.     Compile the keras model

5.     Train the keras model with the dataset

6.     Make predictions using the model

EXPLANATION

You need to fix the import statement for Sequential and Dense. They are on the same line, which will cause a syntax error.

The for-loop should be properly indented.

In model.predict(X), it's best to use .predict_classes() for binary classification problems if you're using older versions of Keras, or you can use a threshold check (> 0.5) for newer versions of TensorFlow/Keras. 

Explanation of changes:

1. Import Fix: Fixed the import statement for Sequential and Dense on separate lines.
2. Prediction Handling: The prediction values are checked against 0.5 (for binary classification), and then converted to integer values (astype(int)).
3. For-loop Formatting: Fixed indentation for the for loop to print the first five predictions correctly.