Ever wondered how big companies put price on their products ? If yes, read on — Parents hardly talk about these things nowadays, all they are concerned about is their kids not getting enough smartphone screen time and social media. The lines above are obviously an attempt of sarcasm but what may qualify a slightly more serious would be this question: When was the last time…

Durbin-Watson may be traditional but it surely surprises — Durbin Watson is more powerful but there is a catch. Read on to know more. When it comes to statistical testing, one of the most important factors that we look for is the power of the test, which may be briefly defined as follows: Power of a test: The probability…

A statistical check on how fair were the dice used by Shakuni — Mahabharata is an ancient Indian epic that narrates a story of an establishment known as Hastinapur. The focus of the story is the two groups of cousins (Kauravas and Pandavas)who ultimately went for war against each other. The story beautifully describes the development of each character and the dilemmas of…

The sequence of model training in Machine Learning explained — Not only Model Training, everything in life demands a sequence. Take an example of lighting a gas stove: 1) You turn on the gas pipeline valve to the stove. 2) You switch on the knob of the stove. 3) You pass a spark to light it. Can you rearrange the…

Three simple functions to make data analysis through Pandas easy — Pandas is an extensive Python library used by Data Scientists in a varied number of fields. If you have worked in Microsoft Excel or MySQL, you are already familiar with relational data structures. You must be comfortable with the data arranged in rows and columns. I came to know about…

A dumb approach to DBSCAN, an unsupervised machine learning algorithm — This article is also published here DBSCAN stands for Density-Based Spatial Clustering Application with Noise. It is an unsupervised machine learning algorithm that makes clusters based upon the density of the data points or how close the data is. That said, the points which are outside the dense regions are…

Basic explanation with example to illustrate — This article will try to: Discuss the idea behind logistic regression Explain it further through an example What you are already supposed to know Basic Probability Theory Linear Regression Sigmoid function You are given a problem of predicting the gender of a person based on his/her height. To start with…

A simple explanation accompanied with graphs to make the concept lucid — Regression is most probably the first machine learning algorithm that one learns. It is basic, simple and simultaneously a very useful tool that solves a lot of machine learning problems. This article is about Ridge Regression, a modification over the Linear Regression to make it more suitable for feature selection…

Graphically explained the basics of K-Means Clustring in simplest possible manner — This article will try to: Explain graphically the basics of K-Means Clustering, an unsupervised machine learning algorithm Discuss the method of finding optimum value of K and centroid location of the clusters What you are already supposed to know: · Basic mathematics and Euclidian geometry In machine learning, one of…