=================================================================================

The trained model can be used to make a prediction by:
        myPrediction = model.predict(input_data, steps=2)
where,
        myPrediction -- Returns a Numpy array of predictions.
        .predict -- With this method, we can pass:
                 i) A Dataset instance,
                 ii) Numpy array,
                 iii) A TensorFlow tensor, or list of tensors,
                 iv) A generator of input example.
                 v) steps – Determines the total number of steps before declaring the prediction round finished. Here, steps = 2 since there are only two examples.

With a Keras model for training, the significance of the .fit() method is that it can define the number of epochs.

===================================================

Machine learning: KNN algorithm: code:
        
Input:        
        
Output:        
        

===================================================

Machine learning: KNN algorithm (version 3 -- more functions are added): code:
        
        
Input:        
        
Output:        
                
                

============================================