Machine Learning for Smart Services
Full course descriptionSmart services or (more generally) intelligent systems rely on data to automate processes or assist human decisions. There are numerous domains in which they are applied such as predictive maintenance and recommender systems. They all have a set of components in common: input, output and a controller, but they vary on different aspects: such as the level of automation, ranging from suggesting actions to a user to automated, autonomous actions.
After following Machine Learning for Smart Services you will understand the concept of intelligent systems, such as what constitutes them and when they are useful to implement. Building on the knowledge you gained in the course Business Analytics you will learn how to implement and evaluate them.
Course objectivesAfter completing this course you:
* Know the relationship between machine learning, artificial intelligence and smart services.
* Will be able to design and implement intelligent systems.
* Will be able to reflect on and evaluate intelligent systems.
Prerequisites* Experience with programming in R
* Basic understanding of predictive modeling and model evaluation
Recommended reading* Hulten, Geoff (2018). Building Intelligent Systems: A Guide to Machine Learning Engineering. New York, NY: Apress [ISBN 978-1-4842-3431-0]
* Additional Papers