Which Python library is commonly used for implementing Support Vector Machines (SVM)?Answer areapandasscikit-learnNumpyTensorFlow

The Python library commonly used for implementing Support Vector Machines (SVM) is scikit-learn. Scikit-learn is well-known for its simplicity and effectiveness in various machine learning tasks, including classification, regression, and clustering, making it a popular choice among data scientists and machine learning practitioners.

While libraries like TensorFlow and Keras also support SVM implementations, scikit-learn has a more straightforward, user-friendly interface specifically for SVM and other classic machine learning algorithms. pandas and Numpy, on the other hand, are primarily used for data manipulation and numerical computations rather than directly implementing SVM.