Machine Learning Lab JNTUK R23 · IT · semester 3-2 · syllabus

This JNTUK R23 professional core course is listed for Information Technology (IT). It is listed in semester 3-2. It carries 1.5 credits. Its published Machine Learning Laboratory Experiments section lists 14 activities or topic groups.

Offered in

Branches	Semester	L	T	P	C
IT	3-2	0	0	3	1.5

SOURCE DOCKET

Published evidence

✓ Verified

Source

• Official JNTUK syllabus ↗ jntuk.edu.in

Checked

12 Jul 2026

Record

1 published section

Verification scopeSubject name, credits, and published laboratory experiment list are sourced directly from JNTUK's official R23 course structure and syllabus document.

Published practical or activity coverage: Machine Learning Laboratory Experiments. Tick it off as you cover it — your progress stays on this device.

Unit-wise syllabus

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UNIT 01 — Machine Learning Laboratory Experiments Compute mean, median, mode, variance and standard deviation · Apply attribute selection, missing-value handling, discretization and outlier removal · Apply K-nearest neighbours to classification and regression · Use and tune a decision tree for classification · Use a decision tree for regression · Apply random forests to classification and regression · Demonstrate Naive Bayes classification · Apply a support-vector algorithm to classification · Demonstrate simple linear regression · Apply logistic regression to classification · Demonstrate a multilayer perceptron for classification · Implement K-means and evaluate performance using within-cluster Euclidean distance for different values of K · Demonstrate fuzzy C-means clustering · Demonstrate expectation-maximization-based clustering