Explain the concept of hypothesis space and inductive bias in brief.
List and explain perspectives and issues in machine learning.
Define artificial neural network. Explain the biological learning system.
Describe the characteristics of back propagation algorithm.
Define Decision tree learning. List and explain appropriate problems for decision tree learning.
List and explain the issues in Decision tree learning.
Illustrate K. means clustering algorithm.
Write K means algorithm and separate { 5, 11, 19, 27, 23, 25, 6, 18, 2, 8, 10, 12, 31, 29, 4 } into 3 clusters.
Explain resampling methods in machine learning.
Explain the concept of measuring the classifier performance.
Distinguish between Supervised machine learning and reinforcement learning.
Explain the multi-layer perceptron model with a neat diagram.
Explain parallel processing perception learning in neural networks.
What is the goal of support vector machine (SVM)? How to compute the margin.
Describe the following: a) Logistic Regression b) Issues in machine Learning c) Requirements of clustering algorithms
