This is my note for ISYE 8803. This course focuses on analysis of high-dimensional structured data including profiles, images, and other types of functional data using statistical machine learning. A variety of topics such as functional data analysis, image processing, multilinear algebra and tensor analysis, and regularization in high-dimensional regression and its applications including low rank and sparse learning is covered. Optimization methods commonly used in statistical modeling and machine learning and their computational aspects are also discussed.

Machine learning plays a vital role in trading by enabling the analysis of vast amounts of financial data and the development of predictive models. It leverages algorithms and statistical techniques to identify patterns, make predictions, and generate insights for informed trading decisions. Machine learning algorithms can be applied to various aspects of trading, including price prediction, risk management, portfolio optimization, market analysis, and automated trading. By leveraging machine learning, traders can uncover hidden patterns in data, adapt to changing market conditions, and improve decision-making processes, ultimately aiming to achieve better trading performance and profitability.