A Numpy array is a grid of values, all of the same type. These values contain information about each pixel of the image. It is the primary information stored in the pixels and determines the intensity of light from each point of the image. Because images are Numpy arrays, arithmetic operations can be performed on them like any other array.
To have a hands-on-experience as you read, I recommend you install these python libraries: NumPy, Matplotlib, Scipy, and Scikit-image.
Let’s start by generating a Numpy array of random integers.
Imagine two of your friends, Lisa and John, call you during the weekend at separate times. After the second call, you got to know both weren’t feeling so well and also realized both shared similar symptoms. Lisa, who lives in the U.S expressed that, she felt feverish, has chills and headaches. She hasn’t been to the hospital yet and is wondering what might be wrong with her. John, who also called you, a couple of hours after Lisa called, only expressed that he felt “small” chills and even said it wasn’t any big deal. John lives in Nigeria.
Classification and regression tree (CART) is a decision tree learning algorithm used for building predictive models from datasets. The models are built by recursively splitting the dataset with true or false questions which provides thresholds for the split. The splitting aims to produce a distribution of pure labels as the tree grows. We will explain what we mean by “pure labels” as we read on.