Dive into a comprehensive lecture on expression analysis, clustering, and classification in machine learning and computational biology. Explore fundamental concepts like machine learning, Bayesian inference, and various clustering techniques. Understand the distinctions between AI, ML, representation learning, and generative AI. Learn about practical applications in gene expression analysis, including K-means clustering, Gaussian mixture model sampling, and hierarchical clustering. Discover methods for clustering documents and free-form text, and gain insights into Naive Bayes classification. This in-depth presentation covers essential topics in computational biology and machine learning, providing a solid foundation for further study and application in the field.