CSCI 0451 Final Project: Create a machine learning model that predicts a players bat speed utilizing Recursive Feature Elimination, Linear Regression and Random Forest Regression models.
A blog post discussing the fairness of a prediction algorithm with respect to demographic characteristic bias.
A blog post reflecting on the work of Timnit Gebru.
Implementing least-squares linear regression and experimenting with LASSO regularization for overparameterized problems, CSCI 0451.
Implementing kernel logistic regression, a method for using linear empirical risk minimization to learn nonlinear decision boundaries, CSCI 0451.
Implementing simple gradient descent and stochastic gradient descent, comparing their performance for training logistic regression, CSCI 0451.
Implementing the perceptron algorithm using numerical programming and demonstrate its use on synthetic data sets, CSCI 0451.