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• The dataset might contain redundant data at times, which does not have any reference while creating a decision
                 tree. Therefore, only those parameters that affect the output directly must be included.
                 • While making decision trees, one should take a look at the dataset given to them and try to figure out what
                 pattern the output leaf follows. Try selecting any one output and on its basis, find out the common links that all
                 the similar outputs have.


              Pixel It—Learning-Based Approach
              In computer vision applications, understanding pixels, resolution, and megapixels is crucial for processing images.

              The pixel is the smallest unit of digital images or displays. It is a tiny dot (smallest point) in a graphic image that
              stores colour and intensity details. Pixels work together to create the graphic that you view on your screen.
              Resolution refers to the clarity or sharpness of a picture or text seen on the display. It is the total number of pixels
              (tiny dots) that comprise the display. A higher resolution involves more pixels, which leads to an improved and
              more accurate image.
              The term megapixel refers to the resolution of digital cameras and camera sensors. It indicates one million pixels.
              For example, a 16-megapixel camera can capture photographs with a resolution of about 4928 x 3264 pixels that
              contain approximately 16 million pixels.
              Calculating the number of megapixels in an image involves a simple formula based on its resolution. The formula is:
                                                          Width in pixels × Height in pixels
                                          Megapixels =
                                                                     1,000,000

              "Pixel It" is an example of a machine learning approach that is used in computer vision applications. The graphics
              or images created on computers are pixel-based images. It shows how the computer classifies the images and
              reads them.

              Let us do an activity that helps us understand how the images are processed and classified by the computers.


                               Task                                                #Experiential Learning



                   An image has a resolution of 3264x2448 pixels. Calculate the number of megapixels in this image.











                       What is Evaluation?

              Model evaluation is the stage of testing the model where testing data is given to the system and the output
              generated is evaluated with the actual result to see the accuracy of the output and the reliability of the AI model.
              There can be different evaluation techniques, depending on the type and purpose of the model.


              Importance of Evaluation
              Evaluation is a process that critically examines a program. It involves collecting and analysing information about
              a program’s activities, characteristics, and outcomes. Its purpose is to make judgements about a program, to
              improve its effectiveness, and/or to inform programming decisions. Following are some of the advantages of
              evaluating an AI model:

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