1.using the history object in the source code, plot the loss and accuracy for both training data and validation data.

2. plot one of the images in the test data and then do inferencing to check what is the prediction of the model on that single image in the test data

3.We had used 2 hidden layers and relu activation:
  a. Try to change the number of hidden layers and the activation to tanh or sigmoid and report what happens.

After adding more hidden layers the accuracy increased

4. Run the same code without scaling the images, how the accuracy changes?

After training with unscaled data, the accuracy got declined from 95% to 52%

** Bonus point:
5. Convert the sequential model to API model.

By
DUKKIPATI SRI SAI NITHIN CHOWDARY
Class id: 4
Team id: 6