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23CST303-MACHINE LEARNING

By SHOBANA Categories: CSE

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Machine Learning

Course Content

Syllabus

Syllabus

Lecture Notes

UNIT I – Introduction
unit 1.2 ML Pipeline
1.3 ML Concepts
1.4 Application of ML
1.5 Dataset Types
1.6 Train-Test Split
1.7 Features and Labels
1.8 Features and Label
Unit 2 – 2.1 Linear Regression
2.2 Regression & Classification
2.3 Polynomial Regression
2.4 Logistic Regression
2.5 Logistic Regression – Example
2.6 KNN
2.7 Decision Tree
2.8 Naive Bayes
2.9 Underfitting – Cross validation
3.1 SVM
3.2 Random Forest
3.3 Ensemble Methods
3.4 PCA
3.5 Dimensionality Reduction

Puzzle

UNIT I
UNIT II

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Intermediate
1 Total Enrolled
March 24, 2026 Last Updated
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