# SVM2

**Repository Path**: tafkap_1981/svm2

## Basic Information

- **Project Name**: SVM2
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-05-19
- **Last Updated**: 2024-05-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# PRODIGY_ML_03
Implement a support vector machine (SVM) to classify images of cats and dogs from the Kaggle dataset.
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Dataset:  https://www.kaggle.com/datasets/chetankv/dogs-cats-images
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I have used 500 sample images per category, and 80% of them for training. <br> Accuracy can be increased by increasing dataset containing thousands of images and number of relevant tokens.
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t1.jpeg - t4.jpeg are the images I used to check output.


<br>My linkedin profile <br>
http://www.linkedin.com/in/jakirhussain28
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