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3.  Matplotlib uses a built-in function piecharts() to create pie charts.                   ….…………….
                    4.  Web Recommendation uses KNN algorithm.                                                  ….…………….

                    5.  Personality prediction trait uses Machine Learning algorithm.                           ….…………….

                 D.  Match the following:
                    1.  Google search                               a.  Pokémon GO

                    2.  Virtual reality                             b.  System maps

                    3.  Fraud and risk detection                    c.  Meaningful information
                    4.  Data features                               d.  Applications of Data Science

                    5.  Data exploration                            e.  Banking sector

                                                  SECTION B (Subjective Type Questions)

                 A.  Short answer type questions:

                    1.  In what ways data science is helpful to the airline industry?
                   Ans.  Data Science really proved to be a boon to this industry as it helped to:
                          • Predict flight delay.

                          • Decide which class of airplanes to buy.
                          • Whether to directly land at the destination or take a halt in between.
                          • Effectively drive customer loyalty programs.
                    2.  Explain the term Outliers Data. Give an example.
                   Ans.    Outliers  means  the  data  that  differs  drastically  from  the  rest  of  the  data.  This  kind  of  unusual  data  needs  to
                       be removed or replaced from the dataset for accurate results. For example: value zero given in marks of a student who
                       is absent instead of exemption. This will not give an accurate class average.
                    3.  What type of data can be used by Pandas?
                   Ans.  Pandas can be used for the following:
                          • Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet
                          • Ordered and unordered (not necessarily fixed-frequency) time series data.
                          • Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels.
                          • Any other form of observational / statistical data sets.
                    4.  Why is KNN called a lazy learner algorithm?

                   Ans.   KNN is also called a lazy learner algorithm because it does not learn from the training set immediately instead it stores
                       the dataset and at the time of classification, it performs an action on the dataset.


                 B.  Long answer type questions:
                    1.  What are the important points to remember when data is collected?
                   Ans.   While handling data online or offline, the following points to be always remembered:
                          • The source of data should be authentic and reliable, as the random data source could provide wrong or unusable
                         data.

                          • For proper training of AI Model, the authenticity of data is must.
                          • Privacy of data sources should always be kept in mind, as it is a fundamental right of everyone.





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