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Practical Machine Learning with R and Python – Part 2

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In this 2nd part of the series “Practical Machine Learning with R and Python – Part 2”, I continue where I left off in my first post Practical Machine Learning with R and Python – Part 2. In this post I cover the some classification algorithmns and cross validation. Specifically I touch-Logistic Regression-K Nearest Neighbors (KNN) classification-Leave out one Cross Validation (LOOCV)-K Fold Cross Validationin both R and Python. As in my initial post the algorithms are based on the following courses. You can download this R Markdown file along with the data from Github. I hope these posts can be used as a quick reference in R and Python and Machine Learning.I have tried to include the coolest part of either course in this post. The following classification problem is based on Logistic Regression. The data is an included data set…
Original Post: Practical Machine Learning with R and Python – Part 2