The importance of blending DevOps best practices with MLOps, and the challenges of separate DevOps and MLOps pipelines.

Topics covered include data preprocessing, data warehouse, association, classication, clustering, outlier detection, and mining specific data types such as time-series, social networks, multimedia, ...