During the Spring 2019 semester I took two classes. In addition to Applied Machine Learning I took Cloud Computing Applications where we learned about everything from AWS Infrastructure, Docker, Hadoop, HBase, Kafka, Spark and many other Cloud and Big Data technologies. This course consisted of a about 10 self paced quizzes and 4 “machine problems” or MP’s as they are are referred to at UIUC. These are coding exercises. For the final project we took this opportunity to build a large scale deep learning convolutional neural network.
This was an awesome project where I worked with a research group to train a supervised Convolutional Neural Network model on 122 GB of photographs from AffectNet using PySpark, Pandas, OpenCV, Keras, NumPy, and a whole lotta cloud compute.
Check out my group’s full research paper.