Machine Learning Basics: Supervised v Unsupervised

Check out watsonx: https://ibm.biz/BdvDnY AI and machine learning can help transform a massive pile of data into useful insights. Understanding which branch of machine learning to use – supervised or unsupervised – is key to getting the most impactful analysis. IBM’s Mark Sturdevant identifies the key differences and explains concepts like clustering, regression analysis, and dimensionality reduction. 00:00 - Introduction 00:15 - Differences between supervised and unsupervised machine learning 1:02 - Supervised machine learning examples: binary classification, multi-class classification, and regression 3:13 - Unsupervised machine learning examples: clustering, association, and dimensionality reduction 5:05 - Which approach is right for you? 5:43 - Resources to help you get started