Machine Learning - R_23 - JNTUK, Model Paper - 2
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY KAKINADA B.Tech III Year II Semester – R23 Course: MACHINE LEARNING Time: 3 Hours Max Marks: 70 SECTION – I (50 Marks) Answer ALL questions (Each question carries 10 marks: a) 5 + b) 5) UNIT – I : Introduction to Machine Learning 1. a) Define Machine Learning paradigms. Explain supervised and unsupervised learning with real-world examples. (5M) b) Explain Types of Data used in Machine Learning. How does data type affect algorithm selection? (5M) 2. a) Explain Data Representation in Machine Learning. Discuss different forms of representing data. (5M) b) Describe Model Selection and Model Learning. Explain their role in building an effective ML system. (5M) UNIT – II : Nearest Neighbor–Based Models 3. a) Explain Proximity Measures and Similarity Measures used in nearest neighbor models. (5M) b) Apply Manhattan and Euclidean distance measures to find the nearest neighbor for a given test instance. ...