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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
Introduction to AI 115

