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BreastCancerDEtection_SVM
Breast Cancer Analysis Using Support Vector Machine SVM works by mapping data to a high-dimensional features space so that data points can be categorized, even when the data are not linearly separable. A separator between the categories is found, then the data is transformed in such a way that the separator could be drawn as a hyperplane.
Certifications
ML_ALGOS
Machine Learning Algorithms with Python Codes
Quantium-module1
The-Spark-Foundation
Data Science And Business Analytics
Danish-kaur's Repositories
Danish-kaur/BreastCancerDEtection_SVM
Breast Cancer Analysis Using Support Vector Machine SVM works by mapping data to a high-dimensional features space so that data points can be categorized, even when the data are not linearly separable. A separator between the categories is found, then the data is transformed in such a way that the separator could be drawn as a hyperplane.
Danish-kaur/Certifications
Danish-kaur/ML_ALGOS
Machine Learning Algorithms with Python Codes
Danish-kaur/Quantium-module1
Danish-kaur/The-Spark-Foundation
Data Science And Business Analytics