This assignment requires applying advanced classification algorithms to the MNIST dataset and conducting an in$-$

depth regression analysis on the California housing dataset. Each task must demonstrate not only technical

proficiency but also strategic thinking and ethical considerations.

Tasks

$1.$ Advanced Dataset Preparation

$$ Split the MNIST dataset into training and testing sets using scikit$-$learn functions or your own

custom function. Include detailed comments to explain your process.

$$ Conditions:

$$ Use your first name for the training set and your last name for the testing set variable

names. For instance, If your name is john doe, use john$\_$train and doe$\_$test as your

variable names.

$$ Use the last two digits of your student ID as the random$\_$state for any function that requires

it$.$ For instance, the value for the random$\_$state $=[$Last two digits of your student ID$]$

$$ Utilize advanced preprocessing techniques to enhance model performance, such as feature scaling

and dimensionality reduction where appropriate