Practical Applications in Machine Learning (PAML)

3.0 credits · Graduate

This course provides hands-on experience developing and deploying foundational machine learning algorithms on real-world datasets for practical applications including predicting housing prices, document retrieval, and product recommendation, and image classification using artificial neural networks. Students will learn about the machine learning pipeline end-to-end including dataset creation, pre- and post-processing, preparation for machine learning, training and evaluating multiple models. Students will focus on real-world challenges at each stage of the ML pipeline while handling bias in models and datasets.