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hello people from the future welcome to normalized nerd i know its been a year since i uploaded my last video but as i mentioned in my community post a lot of things happen in my life in the past year and i was super busy with it but finally i am here with a new exciting video in this video im gonna talk about feature scaling and normalization and hopefully ill be able to clear some misconceptions along the way so without any further ado lets get started first of all lets see what feature scaling really is for that we need a feature suppose x is a continuous feature from a raw data set and we havent performed any preprocessing on it to visualize the distribution of x lets plot its histogram now im going to divide every value of x by 2 and this shrinks the histogram well this was an example of feature scaling where we literally scale the feature by half we can also subtract a number first and then divide it by another number here i am subtracting by 7 and then dividing by 2 thi
