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data  is  then  fed  to  the  subsequent  hidden  layer.  There  can  be  multiple  hidden  layers  depending  upon  the
        complexity of the function to be performed by the model. The processed data by the hidden layers is passed
        onto the output layer which then gives the final output to the user. No processing is done in the output layer.


                                    Machine Learning                  Machine Learning
                     Data                                                                      Answer
                                 Algorithm + Hidden Rules          Algorithm + Hidden Rules



                                    Machine Learning                  Machine Learning
                     Data                                                                      Answer
                                 Algorithm + Hidden Rules          Algorithm + Hidden Rules



                                    Machine Learning                  Machine Learning
                     Data                                                                      Answer
                                 Algorithm + Hidden Rules          Algorithm + Hidden Rules



                 Types of Neural Networks

        There are mainly two types of Neural Networks:

           • Artificial Neural Network
           • Biological Neural Network
        Now let us learn about them in detail.


        Artificial Neural Networks (ANN)
        It is artificially created efficient computing systems designed to simulate the human brain. It includes machine
        learning as a part of artificial intelligence. An ANN in its training phase is capable of learning by recognising
        patterns in data which is later used to generate the desired output.
        ANN is made up of three basic layers—Input, Hidden and Output. The input layer accepts the inputs, the hidden
        layer processes the inputs, and the output layer produces the result where each layer tries to learn from the
        computed weights. It is the foundation of AI and is used to solve complex problems that are difficult for humans.
        It consists of hardware or software that operates just like neurons of the human brain. Commercial application
        of ANN is in solving complex signal processing, predictions or pattern recognition problems.


        Biological Neural Network
        It is composed of a group of chemically connected or functionally associated neurons. Neurons transmit electrical
        signals to other neurons. These neurons are the building blocks of the complete central nervous system of the
        living body. Brain is the control unit of this neural network.
        An understanding of the biological neural network has led to the development of the Artificial Neural Network
        where these computing systems learn and adapt to the situations and inputs just like Biological Neural Network.


                                                                                              Experiential Learning
                  Video Session

             Visit: https://experiments.withgoogle.com/what-neural-nets-see or scan the QR code.
                    This experiment lets you turn on your camera to explore what neural nets see, live,
                  using your camera. Watch the video explainer above to see how each layer of the
                  neural networks.





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