https://github.com/ljadhav25/support-vector-machine-data-science-
Support Vector Machines (SVM) are supervised learning models used for classification and regression analysis. They are particularly effective in high-dimensional spaces and situations where the number of dimensions exceeds the number of samples. SVMs are also memory efficient as they use a subset of training points called support vectors.
https://github.com/ljadhav25/support-vector-machine-data-science-
matplotlib pandas python skit-learn svc-model svm-model
Last synced: 5 months ago
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Support Vector Machines (SVM) are supervised learning models used for classification and regression analysis. They are particularly effective in high-dimensional spaces and situations where the number of dimensions exceeds the number of samples. SVMs are also memory efficient as they use a subset of training points called support vectors.
- Host: GitHub
- URL: https://github.com/ljadhav25/support-vector-machine-data-science-
- Owner: LJadhav25
- Created: 2024-06-20T09:51:35.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-06-20T09:56:07.000Z (over 1 year ago)
- Last Synced: 2025-01-19T18:11:43.140Z (12 months ago)
- Topics: matplotlib, pandas, python, skit-learn, svc-model, svm-model
- Language: Jupyter Notebook
- Homepage:
- Size: 73.2 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- Support: Support_Vector_Machine(Data_Science).ipynb
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README
# Support-Vector-Machine
With the help of the SVM we will predict weather a customer is going to purchase a product or not based on the age and the estimated salary