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Difference between Deep Learning and Machine Learning is shown below:

                      Parameters                     Machine Learning                         Deep Learning

               Data Dependency           Machine Learning algorithm can easily work  When the size of the data is
                                         with smaller data set.                      small, a Deep Learning algorithm
                                                                                     does not perform well as a deep
                                                                                     learning algorithm needs large
                                                                                     amounts of data to understand
                                                                                     perfectly.

               Hardware Dependency       Machine Learning  algorithms can work  on  Deep Learning algorithms are heavily
                                         low end machines as well.                   dependent on high-end machines.

               Problem Solving           When we  are solving a problem using a  Deep Learning algorithm solves the
               Approach                  traditional  machine learning algorithm it is  problem end to end.
                                         generally recommended that we first break
                                         down  the  problem  into  different  sub  parts
                                         and solve them individually and then finally
                                         combine them to get the desired result.


               Execution Time            Machine Learning algorithms take much less  Usually, Deep Learning  algorithms
                                         time to train.                              take  a  long time to  train  because
                                                                                     there are many parameters making
                                                                                     the training time longer than usual.

              ANN

              ANN stands for Artificial Neural Network. It is made up of neurons that help in image recognition and image
              processing. It uses Deep Learning algorithm that takes an input image, processes it by assigning learnable weights
              and biases to various aspects/objects in the image which will help the system to differentiate one image from the
              other with maximum accuracy. We can say that ANN reduces size, improves features and gives the probability
              value of the input image. They are trained to identify and extract the best features from the images.





                                                                                                  Car



                                Input                   Artificial Neural Network                Output



              Real-world examples of Deep Learning

              Let us learn about some real-world examples of Deep Learning:
                 • Object Identification: Deep learning is used in identifying and classifying objects, animals, or scenes in images.
                Its application can be seen in Google Photos where it automatically categorises images. And in medical imaging
                for detecting diseases like tumors.



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