Reflect on the composition and diversity of the MNIST dataset, considering its impact on the training process

and model performance. Explore how the inclusion of a more diverse set of handwriting samples $($e$.$g$.,$

different handwriting styles, inclusion of characters from non$-$Latin alphabets, or samples from wider age

$3$

groups$)$ might affect the accuracy and generalizability of machine learning models trained for digit

recognition tasks.