https://github.com/syedfaiqueali/ct-562-machine-learning

This repo contains all weekly tasks of ML
https://github.com/syedfaiqueali/ct-562-machine-learning

Last synced: 8 days ago
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This repo contains all weekly tasks of ML

• Host: GitHub
• URL: https://github.com/syedfaiqueali/ct-562-machine-learning
• Owner: syedfaiqueali
• Created: 2024-04-27T15:09:26.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-07-31T17:14:52.000Z (3 months ago)
• Last Synced: 2024-10-08T19:41:30.678Z (30 days ago)
• Language: Jupyter Notebook
• Size: 21.3 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# CT-562-Machine-Learning

This repository contains all the weekly tasks for the Machine Learning course.

- **Week 2**: Linear Regression

  - Introduction to linear regression models and implementation using a medical prices dataset.

- **Week 3**: K-Means Clustering

  - Basics of clustering algorithms and implementation of K-Means on a customer dataset.

- **Week 4**: Advanced K-Means Clustering

  - Further exploration of K-Means, including optimization techniques and evaluation metrics.

- **Week 5**: Haar Feature Extractor

  - Training a Haar feature-based cascade classifier for object detection tasks.

- **Week 6**: HOG (Histogram of Oriented Gradients) Feature Extractor

  - Implementing HOG for object detection and comparing its performance with Haar features.

- **Week 9**: SVM (Support Vector Machine)

  - Understanding SVM for classification problems and applying it to a relevant dataset.

- **Weeks 13 & 14**: Heart Disease Prediction (SVM vs ANN vs CNN)

  - Comparative study of different models (SVM, ANN, CNN) for predicting heart disease.

  - Implementation details and performance evaluation using the heart disease dataset.