CS 5369L or equivalent with a grade of B or higher, or consent of the instructor.
The students will be able to:
• Describe various traditional and modern machine learning and pattern recognition approaches
• Interpret the learning theory behind these methodologies
• Identify the pros and cons of these approaches
• Experiment with state-of-the-art machine learning and pattern recognition software tools
• Analyze and practice machine learning and pattern recognition applications
• Formulate research target problems into machine learning problems and select the optimum machine learning methods to solve the problem
• Demonstrate experimental results clearly and identify their implications
New course effective Fall 2017. Available only for computer science majors.