Mathematics behind Machine Learning – The Core Concepts you Need to Know
Overview Here’s an intuitive and beginner friendly guide to the mathematics behind machine learning Learn the various math concepts required for machine learning, including …
probability
An Introduction to the Powerful Bayes’ Theorem for Data Science Professionals
Overview Bayes’ Theorem is one of the most powerful concepts in statistics – a must-know for data science professionals Get acquainted with Bayes’ Theorem, …
Statistics for Data Science: Introduction to the Central Limit Theorem (with implementation in R)
What is the central limit theorem? What are it’s applications? And how can you implement the central limit theorem in R? Find out in this article!
6 Easy Steps to Learn Naive Bayes Algorithm with codes in Python and R
Note: This article was originally published on Sep 13th, 2015 and updated on Sept 11th, 2017 Overview Understand one of the most popular and …
Creating a flawless winning strategy in a Casino (BlackJack) using Data Science?
Can we create a flawless winning strategy in a Casino using Data Science? Of course not! Otherwise, all the data scientists out there would …
40 Questions on Probability for data science
Introduction Probability forms the backbone of many important data science concepts from inferential statistics to Bayesian networks. It would not be wrong to say …
AV DataFest 2017 – Out in its Full Glory
AV DataFest 2017 – Here we begin !! This April, the world will see a battle fought by data scientists and data managers across …
Basics of Probability for Data Science explained with examples in R
Introduction Statistically, the probability of any one of us being here is so small that you’d think the mere fact of existing would keep …
Launch of AV Casino – An Introduction to Probability
Over the last few months, you would have seen us experimenting with various formats to aid learning and knowledge exchange among our community members. …
Using Platt Scaling and Isotonic Regression to Minimize LogLoss Error in R
Introduction This article is best suited for people who actively (or are aspiring to) participate in data science / machine learning competitions and try …
