Artificial Intelligence, Data Science, Reactive Machines, Limited Memory, Deep Learning, Algorithms, Predictive Analytics, Prescriptive Analytics, Machine Learning Systems
When we think of artificial intelligence, we often are drawn to the self-driving cars, voice-based home technologies and automated online interactions that fill the news and drive our daily activities. However, the root of these advancements, machine learning, is a predictive analytics technique that has much broader applicability. With the age of “big data” and the buzz around “data science” continuing to grow, decision-makers are asking themselves if emerging technologies, such as machine learning, can help improve business processes.
In this seminar we will demystify the fundamental concepts that comprise machine learning. The differences between supervised and unsupervised learning, as well as classification will be illustrated. In addition, we will offer examples that illustrate the use of machine learning in industry via business-driven case studies.
Rainwater, C. (2019). The Role of Artificial Intelligence in Business Decision Making. Operations Management Presentations. Retrieved from https://scholarworks.uark.edu/opmapub/14