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7.  What is a Training Dataset?
                   Ans.  A collection of data provided to a machine learning model to help it analyse and learn patterns is called training data.
                    8.  Name two types of learning-based approaches.

                   Ans.  The two types of learning based approaches are: Machine Learning and Deep Learning.
                 B.  Long answer type questions.

                    1.  Differentiate between Machine learning and Deep learning.
                   Ans.  The difference between ML and DL are as follows:

                       Parameters                  Machine Learning                           Deep Learning
                                      Machine Learning algorithm can easily work with   When the size of the data is small, a Deep
                       Data           smaller data set.                          Learning algorithm does not perform well as a
                       Dependency                                                deep learning algorithm needs large amounts
                                                                                 of data to understand perfectly.
                                      Machine Learning algorithms can work on low
                       Hardware                                                  Deep Learning algorithms are heavily dependent
                                      end machines as well.
                       Dependency                                                on high-end machines.
                                      When we are solving a problem using a      Deep Learning algorithm solves the problem
                                      traditional machine learning algorithm it is   end to end.
                       Problem        generally recommended that we first break down
                       Solving        the problem into different sub parts and solve
                       Approach       them individually and then finally combine them
                                      to get the desired result.
                                      Machine Learning algorithms take much less   Usually, Deep Learning algorithms take a
                                      time to train.                             long time to train because there are many
                       Execution Time                                            parameters making the training time longer
                                                                                 than usual.

                    2.  How does Neural Networks work?
                   Ans.  Neural Networks are made up of layers of neurons, just like the human brain that consists of millions of neurons. These
                       neurons are the core processing units of the network. A Neural Network is divided into multiple layers. Each layer in
                       Neural Network is further divided into several blocks called nodes. Each node has its own task to accomplish which is
                       then passed to the next layer. These layers with their working are as follows:



















                                INPUT                     HIDDEN                     OUTPUT
                                LAYER                      LAYERS                     LAYER

                       a.  Input Layer: The input layer is the first layer of a Neural Network. Its job is to receive raw data from the outside
                         world and pass it into the network. No processing happens at this layer; it simply acts as a gateway for the data to
                         enter the system.
                                                                          Advanced Concepts of Modeling in AI   209
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