yogender-ai/knn-cat-dog-demo

KNN algorithm from scratch for cat vs dog image classification using Python. Machine learning, distance-based classification, and computer vision experiment.

15
/ 100
Experimental

This project helps machine learning students and aspiring data scientists understand how the K-Nearest Neighbors (KNN) algorithm works for image classification. By inputting images of cats and dogs, it demonstrates how the algorithm processes them into numerical data, calculates distances, and then classifies them. It's designed for those learning machine learning to grasp foundational concepts like data quality, noise sensitivity, and the 'curse of dimensionality' in a practical way.

Use this if you are a student or beginner in machine learning wanting to understand KNN's core mechanics and limitations without relying on complex libraries.

Not ideal if you need a high-accuracy, production-ready image classification tool or a pre-built solution for immediate application.

machine-learning-education image-classification-basics data-science-fundamentals computer-vision-concepts
No License No Package No Dependents
Maintenance 6 / 25
Adoption 4 / 25
Maturity 5 / 25
Community 0 / 25

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Last pushed

Jan 07, 2026

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