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Step 2:   The model learns from the labelled data and the next time you ask it to identify a mango, it can do it easily.
                 That’s exactly how supervised learning works.
                 Example 2:

                 One  of  the  first  supervised  learning  algorithms  developed  was  the  e-mail  spam  filter.  Over  time,  it  has  become
                 efficient in identifying spam mails.





                                                                                Spam or Wanted Email?
                                  EARN CASH FAST


                                                                         System detects patterns in Email About
                                                                                likely markers of spam




                                                                                  Detected pattern
                                                                            Emails with "EARN CASH FAST"
                                  "EARN CASH FAST"                           More likely to be spam email.
                                      detected
                                in 10% of Spam emails
                                                                           Can use such detected patterns to
                                 0% of wanted emails                       make automated decisions about
                                                                                   future emails





                 Supervised Learning Algorithms and Their Use
                 There are two algorithms of supervised learning named regression and classification. The regression algorithm
                 generates  a  mapping  function  from  the  given  data.  With  the  help  of  this  mapping  function,  we  can  predict
                 the future data. On the other hand, the classification algorithm is able to determine which set of given data
                 point belongs to by means of a classification function represented by the dotted line. Following are the uses of
                 Supervised Learning:



                                         Estimating Life
                                           Expectancy  Population Growth             Identity Fraud    Image
                                                         Prediction                    Detection     Classification
                                 Market
                               Forecasting

                                Weather
                               Forecasting                             Supervised
                                               Regression               Learning              Classification

                               Advertising
                                Popularity
                                prediction
                                                                                        Customer     Diagnostics
                                                                                        Retention





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