Have you ever wondered why there are different algorithms for every problem? Let us consider a simple example of Linear Regression and Logistic Regression. There are two things that explain why Linear Regression is not suitable for classification. The first one is that Linear Regression deals with continuous values whereas…

Cost functions are functions that measure the performance of a Machine Learning model given a set of data. Take a simple example of a linear regression model. The cost function of a Linear Regression model is given as All the function does is that it calculates the difference between the…

The concept of Mean Normalization and Feature Scaling is least addressed, to say the least. So, by the end of this article, you will be clear with these two concepts. To understand these two concepts we must first answer few questions. What is Feature Scaling? What is Mean Normalization? When…

Neural Networks (NN) is one of the most widely used concepts today in the world. Neural Networks are also known as Artificial Neural Networks(ANN). So what are these concepts and how do they work? Continue Reading! Artificial Neural Networks or better known as Neural Networks is defined as follows Neural…

One of the key problems every machine learning model faces is the problem of over-fitting. So what is over-fitting and how do we minimize it? What is Regularization? By the end of the article, you will be clear with these concepts. To understand these concepts we will have to answer…

In this article we will answer few basic questions in Machine Learning(ML) for beginners to get started! This article is meant to be concise for quick reference. 1. What is Machine Learning? The formal definition of Machine Learning is as follows Machine learning is the science of getting computers to act without being explicitly programmed …