Projects were done under the mentorship of Dr. Christopher Monterola and Dr. Erika Legara.

Students learn about neural networks (NN), the bedrock of deep learning, and how variants are used for predictive analytics—from pattern recognition to image processing to time series forecasting. Students are tasked to construct their own single-layer artificial neural network in Python from scratch which allows them to gain a deeper understanding of how neural networks work. They are also introduced to other types of NNs including deep NNs such as convolutional neural networks, recurrent neural networks, and GANs with tensorflow/keras, which are relevant packages/libraries in the field, among other tools.