Author: Ligency Team

Linear regression has its loopholes in analyzing data across a specific distribution. One of them is having a fixed mean across the whole data. However, quantile >>

Did you know that 85% of career positions are filled through some form of networking? It’s no secret that networking is vital for career success, but >>

The life of a data scientist or business intelligence professional is often a lonely one. With the average company employing only one or two data science >>

In data science and machine learning, regression is an important modeling algorithm that most individuals learn early on. In fact, people often consider linear >>

Artificial Intelligence (AI) is an innovation that has come and will stick around for a very long time. In almost every sector, a form of AI >>

As a data scientist, understanding nonparametric statistics is an imperative. With the growing demand for data scientists, analysts, and data-focused engineers, >>

The world runs on data, from making bank deposits, paying taxes, and even communicating with loved ones. All we do is being captured and mapped out >>

Given that businesses must use data to improve services, increase productivity, and increase sales, Data Science will become interwoven in everything we do in >>