The Naive Bayes is a classification algorithm used for binary and multi-class classification problems. Naive Bayes is based on a probability-based technique called Bayes Theorem. In this chapter, we are going to understand the mathematics behind the Bayes theorem and the working mechanism of the Naive Bayes classifier. Table of Contents The idea…

K nearest neighbors are simple and yet the most powerful supervised machine learning algorithms. The K-NN algorithms are used to solve both classification and regression problems. In this article, we will understand how a K-NN classifier works. Table of Contents Geometric Intuition of KNN Failure Cases of KNN Limitations of KNN The right…

1. Supervised Learning: Definition: In Supervised Learning, the Machine learns on the labeled dataset (ie; input labeled data and output labeled data) Where you explicitly can tell them this is the input data and this is how the output data must be. …

As Artificial Intelligence is the simulation of human intelligence done by machines and programmed by humans, AI becomes an increasing part of our daily lives. Through this article, I am discussing the number of artificial intelligence applications and their future scopes. If you want to know more about Machine Learning…

Introductory Artificial Intelligence is purely math and scientific exercise but when it becomes computational, it starts to solve human problems. Machine Learning is a subset of Artificial Intelligence. ML is the study of computer algorithms that improve automatically through experience. ML explores the study and construction of algorithms that can learn…