Machine Learning Basics: Regression, Classification — GATE RA Topic Guide

Topic Overview

The topic Machine Learning Basics: Regression, Classification is an essential component of the Computing, AI and Machine Learning chapter in GATE RA Part A (Common Core). Candidates must master the theoretical foundations, solve sample problems, and identify shortcuts to answer questions on this topic quickly under exam conditions.

Suggested Study Strategy

• Review standard formulas and theorems associated with Machine Learning Basics: Regression, Classification.
• Solve at least 15-20 practice questions of varying difficulty levels (easy, moderate, hard).
• Go through previous years' solved papers to examine how Machine Learning Basics: Regression, Classification questions were framed.
• Take short timed quizzes to evaluate your accuracy and problem-solving speed.