What is Supervised Machine Learning?
Supervised Machine Learning also known as supervised learning is an AI algorithm that is used to classify, analyze, and predict Input data based on prior data who's is well labeled. The model learns the prior data as it generates newly Included data according to its type with the aid of its previous experience. To put it simply, it is a process where x(input data) is evaluated and categorized into different classes with the data, that has been already uploaded into the system to bring out the desired y(output data).
It is a sub-concept of machine learning and artificial intelligence. It helps real-world problems such as evaluating data and variables into different categories, which can take a long time while working manually.
How supervised Machine Learning works?
Supervised learning uses a continuous practice set to teach models to bring out the desired data. It learns every time one puts in new data to be evaluated. The algorithm works on its perfection throughout loss function, to minimize the errors.
Supervised machine learning can be categorized into two different classes, i.e. Classification and Regression.
Classification uses an algorithm to designate new data(input) into specific categories. It considers Specific data within the prior data and concludes how those data should be labeled.
Regression is used to model the relationship between the output variables with the input variables. To put it simply, it helps us to understand how our dependent variable is responding to the independent variable when other independent variables are held fixed.
Examples of Supervised Machine Learning
Some well-known examples of supervised learning are,
- Linear regression for a regression problem.
- Image recognition. Such as assigning a name to a photographed face(tagging)
- Speech recognition. Voice search, appliance control. Some of the popular speech recognition algorithms can be seen in Amazon Alexa or Google Home.
Machine Learning is an innovative discovery in the field of artificial intelligence. It has simplified many real-world problems as it continuously improvising our day-to-day life.