Data Collection

Data collection is the process of gathering and formatting information in a way that allows us to develop a practical machine learning model. Data is collected from many different sources, and proper data collection is one of the most important parts of developing an effective machine learning model.

Neural Networks

A artificial neural network is a system of algorithms inspired by the biological neural networks in our own brains. In practice, a set of nodes, or neurons, interact with each other through a series of inputs and outputs along edges that connect them. Used properly, an artificial neural network can be a powerful tool in developing machine learning models.

Deep Learning

Deep Learning is a subset of machine learning in which complex neural networks are used to learn on data. Deep learning models are unsupervised, meaning that the data is unstructured or unlabeled. This allows a deep learning model to create features in ways unknown or not understood by computer scientists.


John Gauthier: CSE Major

Sam Kasbawala: CSE Major

Mickey Mannella: CSE Major

Ryan Miller: CSE Major