Page 241 - AI Ver 1.0 Class 9
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11.  Understanding visuals by humans is better than any tabular data format or reports.       ……….……
               12.  Finding out the common links is not important in the decision tree.                      ……….……
               13.  The dataset might contain redundant data at times.                                       ……….……

               14.  Deep learning is a simulation of intelligence in machines.                               ……….……
               15.  The relationship or patterns in the data is not important in Rule-based Approach.        ……….……

                                             SECTION B (Subjective Type Questions)

            A.  Short answer type questions:
               1.  What is AI project cycle?
               2.  What is modelling in AI project cycle?

               3.  Write the names of all the stages of AI project cycle.
               4.  Explain two types of data with examples.
               5.  How sensors are used to collect data?
               6.  Is there any problem in extracting private data?
               7.  Was it challenging for you to draw the decision tree for this dataset? If so, why?
               8.  What is the need of authenticity of the data acquisition method?
               9.  What is Microsoft Power BI?

               10.  What is bubble map?
               11.  What if the dataset had more than 1000 data sets? Will decision tree still be a suitable model for it? Why?
               12.  What is Pixel It?
               13.  What is Learning-based approach?
               14.  Were all the parameters equally important for the Decision Tree? Did you notice any redundant data? If yes, what was it?

               15.  Write one difference between machine learning and deep learning.
            B.  Long answer type questions:

               1.   Explain the concept of AI project cycle with the help of a suitable example.
                  a.  Identification of the goal
                  b.  Designing an algorithm to solve the problem
                  c.  Collection of data in large quantities.
               2.  Create a 4W Project Canvas for the following:

                  Case Study: MIIT Academy is an IT Institute which provides Computer Training to Senior Professionals. The institute has
                  limited seats and is high in demand among the Working Professionals. It is planning to conduct an Entrance Test at Pan
                  India level. They have to ensure that unauthorised people don’t enter the Exam Centers so that they have fair admission
                  selection. For this, they need a system in place that should check who all are entering the center, and the system should
                  raise an alert if it finds any unauthorised person entering. The institute has the hard copies of the photographs of all
                  the professionals who have applied and also all staff would be present at the centers.
               3.  Consider the following scenario/situations:
                  An IT company received a lot of support tickets for their operations. These tickets are categorized into Urgent, Important and
                  Business as usual. The issue faced by the operations is that they are not able to classify them properly which leads to delay
                  in response. Can you think of a classification system to solve this problem? Create a 4W Project Canvas for this purpose.
               4.  Why are system maps used in data acquisition?

               5.  What are the rules for system mapping?



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