Business Applications relying on Unsupervised & Reinforcement Learning

At the end of this course, learners will be able to: • Gain an understanding of popular unsupervised and semi-supervised learning problems including Clustering, Anomaly Detection and Recommender Engines. • Recognise unsupervised learning problems • Solve real business problems, including customer segmentation, quality control and fraud detection use cases, using RapidMiner. • Understand bias and that some supervised classification problems are better solved via Anomaly Detection. • Make a dataset ‘Artificial Intelligence-ready’ using RapidMiner. • Solve real business problems associated with time series or sequential data using RapidMiner. • Understand the complexities of reinforcement learning and dealing with dynamic systems.