Project information

Implementated a neural network mini-library in python, and designed a complete regression neural network trained to estimate housing prices in California based on a collection of general characteristics that were included in the 1990 census. Worked in a team of 4 to explore the effects of various optimizers on model training, and tune the hyperparameters of the final model with a combination of grid search and manual experimentation.