Basic Examples of Anaconda Environments – Predictive Hacks

This post is a gentle introduction about Anaconda Environments which is like the "Docker" of the Machine Learning projects. It is very important when we are working on a project to be reproducible and for that reason, we want to be able to share our working environment with our colleagues, or each project to be in a different environment. Notice that conda supports Python, R, Scala and Julia but we will focus on Python in this post. The open-source Anaconda Distribution is the easiest way to perform Python/R data science and machine learning on Linux, Windows, and Mac OS X. With over 15 million users worldwide, it is the industry standard for developing, testing, and training on a single machine.