A write up of my final project, which uses machine learning models trained on meteorological data from Algeria and Portugal and applies them to assess wildfire risk in the US.
A blog post that trains a logistic regression classifier to predict employment status and then performs an audit of the model to assess racial bias in the model. This post contains some basic exploration of the data, model training, a bias audit of the model, and a discussion of bias within the model and the ethics of employment prediction tools.
A blog post implementing linear regression using both analytical methods and gradient descent, experimenting with LASSO regularization to combat overfitting, and using my linear regression model to analyze trends in a dataset examining bikeshare usage in Washington DC.
A blog post implementing logistic regression with gradient descent. I experiment with stochastic gradient descent versus regular gradient descent, as well as testing different learning rates and batch sizes.
A blog post implementing the perceptron algorithm and testing it on three datasets ranging in complexity and difficulty to classify.
An example blog post illustrating the key techniques you’ll need to demonstrate your learning in CSCI 0451.
