Dale Harrington

Machine Learning Engineers, Data Scientists, and Big Data Engineers rank among the top emerging jobs on LinkedIn. Forbes Data engineering is the process of developing and building systems for collecting, storing, and analyzing data. It is a vast field with several applications in various industries. Firms have collected huge amounts of data, and they require data infrastructure and personnel to sort and analyze the information.

This tutorial explains how to build confidence regions (the 2D version of a confidence interval) using as little statistical theory as possible. I also avoid the traditional terminology and notation such as α, Z1-α, critical value, confidence level, significance level and so on. These can be confusing to beginners and professionals alike. Instead, I use simulations and two keywords only: confidence region, and confidence level.

This article was written by Vasudev. Lets get started quickly. Numpy is a math library for python. It enables us to do computation efficiently and effectively. It is better than regular python because of it’s amazing capabilities. In this article I’m just going to introduce you to the basics of what is mostly required for machine learning and datascience. I’m not going to cover everything that’s possible with numpy library. This is the part one of numpy tutorial series.