Objective: The goal of this assignment is to implement the linear classifier algorithm for image classification using the CIFAR$-10$ dataset. You will:

$1.$Utilize a built$-$in packages or libraries such as Pytorch and Tensorflow to perform forward and backward computations $($Optional$,$ not graded$)$

$2.$Implement the algorithm, such as forward and backward computations independently $($required$).$

Tasks and Requirements:

$1.$Algorithm Implementation: Employ the linear classifier for image classification on the CIFAR$-10$ dataset using a self$-$coded version.

$2.$Performance Improvement Strategies: Analyze how to improve the performance of your implementations, including and not limited to: tuning hyperparameters such as training epoch, step size $($learning rate$),$ regularization terms, strength of regularization, etc. Explore by yourslef!