Support Vector Machine (SVM) is a machine learning algorithm that can be used to classify data. SVM does this by maximizing the margin between two classes, where “margin” refers to the distance from both support vectors. SVM has been applied in many areas of computer science and beyond, including medical diagnosis software for tuberculosis detection, fraud detection systems, and more. This blog post consists of quiz comprising of questions and answers on SVM. This is a practice test (objective questions and answers) that can be useful when preparing for interviews. The questions in this and upcoming practice tests could prove to be useful, primarily, for data scientists or machine learning interns/ freshers/ beginners. The questions are focused on some of the following areas:
Some of the key SVM concepts to understand while preparing for the machine learning interviews are following:
Here are some of the useful posts on SVM you could read for understanding SVM in a better manner:
Here is the list of 15+ questions that can help you test your SVM knowledge, especially, if you are working with Python.
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Here are some of the most asked interview questions in relation to SVM:
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