Facial Recognition Documentation

During this unit, our class collaborated with Pedro Pascal from the AI Institute at the Georgia Institute of Technology. He taught us about deep learning, a type of machine learning in artificial intelligence that uses neural networks with multiple layers to process information and gain a deep understanding of data. Our model utilizes data from a set of images collected over several weeks. Both engineering classes contributed to this dataset by taking pictures, which were then used to train and test the model's accuracy. Essentially, the model employs various imports from the TensorFlow library. It uploads the images from Google Drive and splits the data into training and testing sections. The training set contains the most data and is where the machine learns to predict the names corresponding to the images. The testing set is similar but is used to evaluate the model's performance and accuracy.