CS4315: Introduction to Machine Learning and Data Mining - NPS Online
Introduction to Machine Learning and Data Mining
Course #CS4315
Est.imated Completion Time: 3 months
POC: NPS Online Support
Overview
A survey of methods by which software and hardware can improve their performance over time. Topics include data manipulation, concept learning, association rules, decision trees, Bayesian models, simple linear models, case-based reasoning, genetic algorithms, and finite-state sequence learning. Students will do projects with software tools. Prerequisites: One college-level course in programming.
Included in degrees & certificates
- 268
- 367
Prerequisites
- CY3650
Learning Outcomes
Upon completion of this course the student is expected to:
- Understand of the basic types of learning methods including:
- Caching, case-based reasoning, and decision trees
- Concept learning of logical expressions
- Classification using probabilistic reasoning
- Neural networks
- Heuristic search
- Evolutionary computing
- Generative adversarial learning
- Ensemble learning
- Be able to recommend the most appropriate learning methods for an application
- Be able to explain learning methods with paper and pencil.
- Be able to implement learning methods using a software tool.
- Identify the major difficulties in implementing and testing learning systems, including explaining reasoning, bias, and adversarial attacks.
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