## Activation Functions in ANNs (Part-1)

Introduction In an ANN the activation function of a node is defined as the threshold after which the node will produce an output given an input or set of inputs. Activation functions can be linear or non-linear but mostly nonlinear functions are being used in ANNs. This is a very important in the way a network learns because in light…

## Implementing Principal Component Analysis using Python

This article is in continuation of my previous article on Mathematics of Principal Component Analysis (PCA). It is advised to go through that article before moving into this article. In this post, I will explain how to implement PCA using Python. I have taken the wholesale customer distribution dataset from UCI Machine Learning repository. This dataset refers to clients of…

## Understanding mathematics behind Logistic Regression

Introduction to Logistic Regression Logistic Regression is a type of regression in which returns the probability of occurrence of an event by fitting the data to a mathematical function called ‘logit function’. It is basically a classification algorithm and is used mostly when the dependent variable is categorical, the independent variables can be discrete or continuous. Generalized Linear Models Before starting with…

## Mathematics of Principal Component Analysis (PCA)

Understanding Principal Component Analysis In this part of the article, I will try to explain the mathematics and intuition behind Principal Component Analysis and in the next part, I will show how to implement Principal Component Analysis (PCA) using Python. PCA is an unsupervised machine learning technique which creates a low dimensional representation of a dataset. PCA is used to…