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4.   Assertion (A): Reinforcement Learning is a type of machine learning where a model learns through trial and error
                       to make the best decisions in a given environment.
                           Reasoning (R): In Reinforcement Learning, the agent interacts with the environment, receives feedback in the form
                       of rewards or penalties, and improves its actions based on that feedback.
                     5.   Assertion (A): The Rule-based Approach is one of the earliest and simplest methods of implementing artificial
                       intelligence.
                           Reasoning (R): In the Rule-based Approach, decisions are made based on a set of predefined rules that dictate the
                       system’s actions.
                     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.


                                                                                    21 st  Century   #Technology Literacy
                                                                                        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).


                    2.  Create an Audio Project using the tool.
                        https://teachablemachine.withgoogle.com/
                         Teachable  Machine  is  a  web-based  tool  that  helps  create  machine  learning  models
                        easily, fast and accessible to everyone. The tool allows you to create your own project of Image or
                        Audio or Pose. Once your project is ready you can share, download or upload your project code.

                    3.   Using the link below, experiment with creating some music using those sounds. It’s great
                       fun, try it.
                        https://experiments.withgoogle.com/ai/drum-machine/view/
                         Infinite Drum Machine AI tool is a collection of naturally present sounds from all over the world like the
                       chirping of birds, noise of an airplane, barking of dogs, ambulance siren, playing of drums, etc.












              Answers


              Exercise (Section A)
              A.    1.  b.   2.  d.   3.  b.   4.  b.   5.  c.   6.  c.   7.  b.   8.  d.    9.  c.   10.  b.
              B.  1.  learning-based       2.  historical          3.  Clustering      4.  Regression
                  5.  nodes                6.  large               7.  machine learning   8.  Deep

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