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6.  Assertion (A): A Neural Network is divided into multiple layers, each further divided into nodes.
                          Reasoning (R): Nodes perform tasks and pass the results to the next layer.

                     7.  Assertion (A): Regression is a mathematical approach to find a relationship between two or more variables.
                          Reasoning (R): Regression works with continuous data.



                               In Life                                                    21 st  Century   #Critical Thinking
                                                                                              Skills

                 In what ways do Deep Learning and Natural  Language  Processing revolutionize communication, from voice
                 assistants to healthcare diagnostics, improving efficiency and accessibility?





                             Deep Thinking                                                21 st  Century   #Critical Thinking
                                                                                              Skills

                  Imagine a scenario in which you have been assigned the task to create a robot which would serve as a security
                  in-charge of your school. The robot can think on its own and can take independent decisions. But, before you
                  can start testing your robot in the school, you have to pass a test which shows that your robot won't pose a
                  threat to the students of your school. What do you think would be the hurdles that your robot needs to clear
                  before it is ready?


                                                                                            #Technology Literacy
                                                                                    21 st  Century
                                                                                       Skills  #Media Literacy
                                Lab


                       1.  Using the   link below,  experiment  with  adjusting different  parameters  like learning  rate,  number  of
                          neurons, activation functions, etc., to observe how the model's performance changes.
                          https://playground.tensorflow.org/
                          Now, summarise what you learned about the role of each component in the network
                          (e.g., activation functions, hidden layers, learning rate).































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