Machine Learning

GATE 2026 Machine Learning Crash Course

A free crash course covering core Machine Learning topics for GATE DA, from basics to neural networks.

Learn from: the original creator. Original content published on YouTube. DigitalSkillX organizes these public resources into a structured learning path. DigitalSkillX does not claim ownership or partnership.

Lessons: 0
Level: intermediate

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About this path

This learning path follows a GATE 2026 crash course on Machine Learning for the Data Analytics (DA) stream. It starts with an introduction to ML, then moves through regression, classification, decision trees, SVM, KNN, Naive Bayes, clustering, dimensionality reduction, and neural networks. Each lesson is designed to match the GATE DA syllabus, with exam-focused explanations and practical examples.

What you will learn

Understand core ML concepts and types of learning
Apply linear and logistic regression for prediction and classification
Build and interpret decision trees and random forests
Explain SVM, KNN, and Naive Bayes algorithms
Perform clustering with K-Means and hierarchical methods
Use LDA and PCA for dimensionality reduction
Understand the basics of neural networks

Who this is for

Self-paced learners who want a clear free path with creator-credited YouTube lessons.

Curriculum

Your progress

0 of 0 lessons completed.

Complete this learning path to become eligible for your DigitalSkillX certificate.

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