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i.   Your model must detect patterns in images.
        ii.  False forecasts can have disastrous effects. Errors can be fatal in such a case.
        iii.  It may take up to an hour to reveal the outcome; so the motto "Take your time, but be precise." must be followed.
         an you see ho  different cases result in different demands   he desired output type also shifts. In the first scenario, you
         ant a te t output  in the second, you  ant a categorisation classification   the patient is healthy or not.
         coping a problem is difficult because  e need to have a deeper understanding of it so that the image gets clearer as
        we attempt to solve it. As a result, we employ the 4Ws Problem Canvas to assist us in identifying the important factors
        associated with the problem.
        Using the 4Ws problem canvas, the problem statement can be formulated as follows:


                      The                          [the stakeholders]       Who
                      have a problem that          [issue, need]            What
                      when/while                   [situation/location]     Where
                      A good solution using AI would   solution benefit     Why
        Hence, in the future, whenever there is a need to look at the foundation of the problem again, we can take a look at the
        Problem Statement Template to understand its key elements.
                                                                                             Experiential Learning

                    Video Session

               Scan the QR code or visit the following link to watch the video: 4Ws of Problem Scoping in AI Project
               Cycle | The 4Ws Canvas | Aiforkids
               https://www.youtube.com/watch?v=qFoIxZPt9Ho
               After watching the video, answer the following question:

               What have you learnt from this video?










        Data A cq uisition
         o  undertake  data  analysis,  one  must  first  collect  data  from  credible  sources.   eal  orld  data  can  be  strange  and
        deceptive. Human entries are always prone to mistakes, such as someone mistyping 40.0 as 400, someone spelling
        something, or labeling the data incorrectly. Hence, the data needs to be relevant and authentic. Authentic data can be
        gathered from a variety of sources, including:
        •   government websites                    •   devices such as cameras and sensors

        •   purchases, transactions, registrations    •   other public surveys and records

        Data Ex plor ation
        After gathering data, processes such as:
        •   data cleaning to locate missing values

        •   eliminating worthless data (erroneous samples and outliers)
        To know more about data cleaning techniques go through the following link:
        https://towardsdatascience.com/data-cleaning-techniques-in-microsoft-excel-you-need-to-know-
        4075cbb30731
              158     Touchpad Artificial Intelligence (Ver. 2.0)-XII
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