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3. Write a table of comparison for Linear regression- single and multi-variable, Logistic regression, KNN, Support Vector Machines, Decision Trees, and K-means in terms of

3. Write a table of comparison for Linear regression- single and multi-variable, Logistic regression, KNN, Support Vector Machines, Decision Trees, and K-means in terms of algorithm description, process, evaluation, accuracy, advantages and dis-advantages. 4. Implement a K-means algorithm on real time-application, using available dataset.

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