This JNTUK R23 professional elective is listed for Electronics and Communication Engineering (ECE). It is listed in semester 3-2. It carries 3 credits. The published coverage runs across 5 units, from Introduction to Machine Learning through Model Evaluation and Visualization.
Verification scopeSubject name, credits, unit-wise syllabus, and course outcomes are sourced directly from JNTUK's own official R23 course structure and syllabus document, not an autonomous college's adaptation.
What you'll be able to do
Define machine learning and its different types and understand their applications.
Explain the various techniques involved in pre-processing of data for Data Analysis
Apply various supervised learning algorithms including decision trees and k-nearest neighbours (k-NN) etc.
Implement unsupervised learning techniques, viz., K-means clustering etc.
Learn about various performance metrics and explore them in various applications of implementing Machine learning Algorithms.
5 units, from Introduction to Machine Learning to Model Evaluation and Visualization. Tick off units as you cover them — your progress stays on this device.