Splitting the advertising data (advertising.csv) into training and testing data sets, then choosing and training a classification machine learning algorithm; Getting the accuracy of the ML model; Using feature engineering skills to create new features and improve my ML model;
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"Feature engineering and improving the Machine Learning model accuracy;
Using the advertising data: advertising.csv;
The ML model predicts the last column "Clicked on Ad";
Splitting the data into training and testing data sets, then choosing and training a classification machine learning algorithm;
Getting the accuracy of the ML model;
Using feature engineering skills to create new features and improve my ML model;"
Splitting the advertising data (advertising.csv) into training and testing data sets, then choosing and training a classification machine learning algorithm; Getting the accuracy of the ML model; Using feature engineering skills to create new features and improve my ML model;