This course will enable students to
Course | Learning outcome (at course level) | Learning and teaching strategies | Assessment Strategies | |
Course Code | Course Title | CO205. Identify linear and nonlinear problems in an application domain and formulate them for analysis CO206. Select a suitable algorithm to handle nonlinear problems. CO207. Extract dataset, pre-process and transform them for computation. CO208. Design machine learning model to solve the problems and interpret their results. CO209. Evaluate the performance of machine learning models using ML metrics. CO210.Contribute effectively in course-specific interaction | Approach in teaching: Interactive Lectures, Group Discussion, Case Study
Learning activities for the students: Self-learning assignments, Machine Learning exercises, presentations |
Class test, Semester end examinations, Quiz, Practical Assignments, Presentation |
24CBDA412 | Advanced Machine Learning Lab (Practical)
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Exercises based on the following topics:
e RESOURCES
JOURNALS