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5.  What do you mean by a Testing Dataset?
                    6.  Name any four real-world applications of Neural Network.

                 B.  Long answer type questions.

                    1.  Explain the three basic layers of Artificial Neural Network.
                    2.  Explain any four applications of machine learning in our daily lives.
                    3.  Differentiate between supervised and unsupervised learning models.
                    4.  Explain the term association rule with the help of an example.
                    5.  What is regression? Give an example.

                                                                                            21 st  Century   #Information Literacy
                 C.  Competency-based/Application-based questions.                              Skills  #Critical Thinking
                    1.  Identify the type of learning (supervised, unsupervised, reinforcement learning) are the following case studies most
                       likely based on?
                       a.  Case Study 1: A car rental company wants to predict the rental price of vehicles based on features such as car type,
                          rental duration, and location. They have historical rental data with labelled prices.
                       b.  Case Study 2: An online game uses a system where players are rewarded for making progress in the game and
                          penalized for making mistakes. The system learns the best strategies by interacting with players over time.
                       c.  Case Study 3: A robot is learning to navigate a maze by receiving rewards for reaching the goal and penalties for
                          hitting walls, adjusting its actions based on this feedback.
                       d.  Case Study 4: A company wants to identify potential fraudsters by analyzing transaction patterns and customer
                          behaviours, using labelled data of legitimate and fraudulent transactions.
                       e.  Case Study 5: A library wants to analyse patterns in book loans to recommend books to patrons, without predefined
                          categories or labels for the books.
                    2.  A retail store has a dataset containing transaction histories, customer demographics, purchase frequency, and product
                       categories. The tasks involve:
                       a. To predict whether a customer will make a purchase during a promotional campaign.
                       b. To forecast the total revenue for the next month.
                       c. To segment customers based on their purchasing behaviour for targeted marketing.
                       d. To discover frequently purchased product combinations for better shelf placement and promotions.
                    3.  Identify the type of model (classification, regression, clustering, association model) are the following case studies most
                       likely based on?                                                                   [CBSE Handbook]
                       a.  A bank wants to predict whether a loan applicant will "default" or "non-default" on their loan payments. They have
                          a dataset containing information such as income, credit score, loan amount, and employment status.
                       b.  A real estate agency wants to predict the selling price of houses based on various features such as size, location,
                          number of bedrooms, and bathrooms. They have a dataset containing historical sales data.
                       c.  A marketing company wants to segment its customer base into distinct groups based on purchasing behaviour for
                          targeted marketing campaigns. They have a dataset containing information such as purchase history, frequency of
                          purchases, and amount spent.
                       d.  A grocery store wants to identify associations between different products purchased by customers to understand
                          which products are  commonly bought  together.  They have a transaction  dataset  containing records  of items
                          purchased together during each transaction.
                       Assertion and Reasoning Questions:
                       Direction: Questions 4-7, consist of two statements – Assertion (A) and Reasoning (R). Answer these questions by
                       selecting the appropriate option given below:
                       a. Both A and R are true and R is the correct explanation of A.
                       b. Both A and R are true but R is not the correct explanation of A.
                       c. A is true but R is false.
                       d. A is false but R is true.


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