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<speak> I think<break strength="strong"/> you have completed<break strength="strong"/> your machine learning course.<break strength="x-strong"/> So you might be aware of all these terms<break strength="weak"/> used here. <break strength="x-strong"/> Let's run the cell. <break strength="x-strong"/> Now, we will import the data set.<break strength="x-strong"/> I will show the path of the file on the computer. <break strength="x-strong"/>Here you can see data set c s v file location.<break strength="x-strong"/> Copy this file path<break strength="strong"/> and paste it here in the jupyter notebook. <break strength="x-strong"/> Now <break strength="strong"/>we need to import the data set. <break strength="x-strong"/>We use the read_csv method<break strength="strong"/> to load the data set.<break strength="x-strong"/> Then we will run the cell. <break strength="x-strong"/> We have imported the data set<break strength="strong"/> and stored it in the pandas' data frame diabetes_df<break strength="x-strong"/> Let's check<break strength="weak"/> the top five rows of the data frame.<break strength="x-strong"/> We have saved this<break strength="weak"/> in diabetes_df. <break strength="x-strong"/>Use the dot head method<break strength="weak"/> to check the top five samples <break strength="weak"/>from the data frame. <break strength="x-strong"/>So here we have pregnancies, glucose, blood pressure, skin thickness.<break strength="x-strong"/> We have insulin.<break strength="x-strong"/> We have a BMI. We have diabetes pedigree function.<break strength="x-strong"/> We have an age.<break strength="x-strong"/> And finally, we have the outcome. <break strength="x-strong"/> Here one means yes <break strength="strong"/>and zero means no. <break strength="x-strong"/> <break strength="x-strong"/> </speak>