PUBH8475: Advanced Topics on Machine Learning

This course covers a range of emerging topics in machine learning, data analytics, and big data. This course will introduce various statistical and computational techniques for prediction and inference. These techniques are directly applicable to Business Analytics, Engineering, and Biomedical Research. Topics include the following: - Data exploration and data science. - Optimization for machine learning. High-dimensional analysis: prediction and inference. - Deep neural network learning: basics (FNN, CNN, RNN/LSTM); advanced topics (Transformers, Diffusion models, etc). - Recommender systems: personalized prediction. - Undirected and directed graphical models. - Unstructured data and text mining: Numerical embedding and language models. - Causal Machine Learning. prereq: Pubh7475 or Stat8053 or a similar course, or permission of instructor; familiarity with programming in R or Python. Credit will not be granted if credit has been received for: STAT 8056

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