I know its Diwali time near by and You are excited

  • Lit Diyas to spread light
  • Enjoy the festive season

Let us consider an interesting game where you will get a chance to play with a candle and generate ways of reaching some outcome.


You are a computer programmer who like to solve real world problems with the help of coding knowledge. Amazingly you constructed something very meaningful and someone liked your code so much that she is ready to pay you for using your code.

Your code got popularised and slowly you had…


Pattern! Patterns! Patterns!

That’s what we are concerned about while running a Data Mining pipeline which helps to find patterns in the dataset collected. But are all patterns interesting. Well, not really. Interesting patterns are the one, which exhibit all or some of the properties mentioned below:-

  • Valid…


When we encounter various ML algos, there are terms which actually have their origin in probability and statistics, work as lexicon for an ML engineer or Data Scientist. We will try to understand the meaning of each term and define them mathematically. Terms include:-

  1. Variance | Standard…


The ultimate goal of machine learning techniques, is to predict the actual probability distribution of data generating process. Now this data generating process could be from any trivial or non-trivial probability distribution and it might not be significant to have any assumption looking at the samples/training data taken from population…


A claim is assumed valid

if its counterclaim is highly implausible

In mathematics there are many techniques for proving your statement to be true. These proofs could actually help in making inferences or decision making as well. Poof by induction, Proof by contradiction or statistical proofs are valued. …


Any machine learning algorithm, generally involves components as Optimisation procedure, cost function, modelling technique and the most important is “Dataset to learn”. Its said that any ML algo performs as good as the dataset it is fed with.

Most of the time that is spent following “Knowledge discovery from data”…


Probability theory is all about measuring uncertainty. But before defining the uncertainty, we should have some object/event whose uncertainty we are talking about.

In this article I will talk about Random Variable, Probability Distribution and some of famous distributions of concern to a machine learning enthusiast.

What is Random Variable(RV)?

A variable that takes…


Recently elections were held in part of some democratic country. Instead of waiting for the final election results, some media channels just went to streets and started asking people about their view on the leader of their choice. This randomly asking people about their choice of interest, reflect the choice…


To understand two different approaches to probability, we should be initially very clear about Probability Theory.

Probability Theory is a mathematical framework for representing uncertain Statements.

In Computer science we rarely talk about uncertainty and take most of the entities to be certain and deterministic.

  • CPU will execute every command that you give to…

Nikhil Verma

Knowledge shared is knowledge squared | My Portfolio https://lihkinverma.github.io/portfolio/

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