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Subject: Software Eng (Grad) (SEIS)
CRN: 21478
Lecture
St Paul: Owens Science Hall 250
Requirements Met:
Software Technical Elective
Machine Learning builds computational systems that learn from and adapt to the data presented to them. It has become one of the essential pillars in information technology today and provides a basis for several applications we use daily in diverse domains such as engineering, medicine, finance, and commerce. This course covers widely used supervised and unsupervised machine learning algorithms used in industry in technical depth, discussing both the theoretical underpinnings of machine learning techniques and providing hands-on experience in implementing them. Additionally, students will also learn to evaluate effectiveness and avoid common pitfalls in applying machine learning to a given problem. Prerequisite: Minimum grade of C- in SEIS 631
3 Credits