COURSE OBJECTIVES
➢ To recognize different key paradigms for machine learning concepts
➢ To familiarize with various classifiers used for machine learning
➢ To understand and differentiate among various supervised learning concepts
➢ To become familiarize with data reduction and feature extraction methods
➢ To apply suitable machine learning algorithms for simple engineering problems
COURSE OUTCOMES
On completion of the course, student will be able to
CO1 - Classify supervised and unsupervised learning
CO2 - Apply appropriate machine learning strategy for any given problem Max.
CO3 - Recommend supervised and unsupervised learning algorithms for any given problem
CO4 - Apply the Bayesian concepts to machine learning
CO5 - Measure existing machine learning algorithms
CO6 - Develop an appropriate machine learning approaches for various challenges.
- Teacher: MUTHIAH M. A
- Teacher: Barani S