Welcome to the Machine Learning and Deep Learning Open Lab Series! During this series, Dr. Namig Abbasov offers seven open labs to introduce participants to core concepts and techniques in Machine Learning (ML) and Deep Learning. These open labs will prioritize intuitive understanding of machine learning algorithms and deep learning approaches. These are intended to complement machine learning and deep learning courses taught at ASU by focusing on intuitive explanations of difficult concepts and examples with analogical illustrations. Below, you will find descriptions for each open lab of the series. Each open lab session is one hour long, allowing us to explore these topics as thoroughly as time permits.

Unsupervised Learning, the fourth lab of the Machine Learning and Deep Learning Series, participants will learn to work with unlabeled data using unsupervised learning techniques. The lab will explore clustering methods, including k-Means and hierarchical clustering, to uncover patterns in datasets. Participants will also learn dimensionality reduction techniques like Principal Component Analysis (PCA) to simplify high-dimensional datasets