Machine Learning — Summer 2025

Define human learning. List down the types of it and explain all of them with suitable example.

Define machine learning. List down the types of it and explain all of them with suitable example.

List state-of-the-art languages/tools in machine learning. Explain any three of them.

Draw the chart for four-step process of machine learning. And briefly explain each block.

Differentiate between k-fold and cross validation.

Draw classification chart for the data types in machine learning. Explain “Ratio” data type with example.

Explain BOX plot and its attributes. List advantages and disadvantages of it.

Find the variance and standard deviation for both samples. Form the value of variance and standard deviation, write comparison comment for samples. Sample 1 values : 44, 46, 48, 45, 47 Sample 2 values : 34, 46, 59, 39, 52

Explain Histogram and its attributes. List advantages and disadvantages of it.

Define overfitting and explain it with detailed example and its plot. List the actions that helps to avoid overfitting.

List partitioning methods for clustering. Explain any one of them with suitable example.

Define underfitting and explain it with detailed example and its plot. List the actions that helps to avoid underfitting.

Explain apriori algorithm for association rule learning.

Explain SVM algorithm with suitable example.

Explain Decision Tree algorithm.

Explain K-means algorithms with suitable example

List types of Regression. And explain any one of them with suitable example. 1/1