Machine Learning Algorithms

Eg; For House price prediction, we first need data about houses such as; square foot, no. of rooms, the house has a garden or not, and so on features. We then need to know the prices of these houses ie; class labels. Now data coming from thousands of houses, their features, and prices, we can now train a supervised machine learning model to predict a new house's price based on past experiences of the model. This algorithm is used to predict the discrete values such as male female, true false, spam not spam, etc. Regression algorithms are used to predict continuous values such as price, salary, age, marks, etc. Another example is Opening emergency hospitals to the maximum prone to accident areas.