Gate Data Science and Artificial Intelligence 2026 | Syllabus of Machine Learning

Welcome to Beyond Neural Networks! In this video, I am sharing the Supervised and Unsupervised Machine Learning topics included in the GATE Data Science & Artificial Intelligence syllabus.

📌 Topics Covered in the Syllabus:
🔹 Supervised Machine Learning

Simple Linear Regression
Multiple Linear Regression
Ridge Regression
Logistic Regression
k-Nearest Neighbors
Naïve Bayes Classification
Linear Discriminant Analysis
Support Vector Machine
Decision Trees
🔹 Unsupervised Machine Learning

k-Means / k-Medoids Clustering
Hierarchical Clustering (Top-down, Bottom-up)
Single Linkage
Multiple Linkage
Principal Component Analysis (PCA)
This video is just an overview of the syllabus topics. Stay tuned for future videos where I will explain these concepts in detail!

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