This post is the third part of the multi-part series on how to build a search engine –

• How to build a search engine – Part 1: Installing the tools and getting the technology stack ready
• How to build a search engine – Part 2: …

Most analytic people would agree that lottery is a tax on the innumerate. However, for this statement to be true, we need to assume that winning numbers (and any combination of digits from these numbers) are truly random. If not, of course smart people are going to find and devise algorithms to increase their odds of winning, and/or will try to sell their magic "winning numbers" to idiots. …

This post is the second part of the multi-part series on how to build a search engine –

• How to build a search engine - Part 1: Installing the tools and getting the technology stack ready
• How to build a search engine - Part 2: Configuring elasticsearch
• How to build a search engine - Part 3: …

1. Introduction

Most tasks in Machine Learning can be reduced to classification tasks. For example, we have a medical dataset and we want to classify who has diabetes (positive class) and who doesn’t (negative class). We have a dataset from the financial world and want to know which customers will default on their credit (positive class) and which customers will not (negative class).

To do this, we can train a Classifier with a ‘training dataset’ and after such a Classifier is…

In this multi-part series, we will explore how to build a search engine. It will be quite powerful and industrial strength. The first part will focus on getting the right tools and getting technology stack ready. We will build this search engine with an AngularJS front-end and use elasticsearch as the computation back end.

This post is the first part of the multi-part series on how to build a search engine –

• How to build a search engine – Part 1: Installing the tools and…

In this article, we revisit the most fundamental statistics theorem, talking in layman terms. We investigate a special but interesting and useful case, that is not discussed in textbooks, data camps, or data science classes. This article is part of a series about off-the-beaten-path data science and mathematics, offering a fresh, original and simple perspective on a number of topics. Previous articles in this series can be found …

Deep learning is all the rage. You hear about it in the news, you read it about it in the news and it’s all over popular culture as well. What’s…

Here is our selection of featured articles and resources, published in the last few days:

• Stacking models for improved predictions - A case study for housing prices 
• Statistical Mistakes and How to Avoid Them …

Here is our selection of featured articles and resources posted since Monday.

• Difference Between Data Scientists, Data Engineers, and Software Engineers - According To LinkedIn
• Has AI Gone Too Far? - Automated Inference…