Useful infos about AI, Machine Learning and NLP for non-developers (1)

Man with Post-it saying A.I.

Although Machine Learning, AI and Deep Learning are not new topics, I have only marginally dealt with them so far. That is changing right now. However, I have come across the following issue: I am completely overwhelmed by the amount of information available and so I have to find my way around. In this series of blog posts I will gradually introduce some sources that have helped and still help me to better understand the topic and to acquire basic knowledge. So, here we go!

AI, Machine Learning, Deep Learning – where to start?

When it comes to Al, I always wondered where to start. Do I have to be a developer to understand anything at all? Is there an easier introduction to the topic without prior knowledge? I’m all about the basics. Fortunately I found this extremely useful, informative medium article by Niklas Donges:
The Non-Technical AI Guide

The topics covered in the article include “Misconceptions about AI”, “What is Machine Learning”, “The Terminology of AI, “What is Data” and more. Fifteen minutes of reading time are well worth it.

What is Machine Learning?

Learning Machine Learning Comic
Source: Learning Machine Learning

I was wondering if this topic can be explained as simple as possible? Google’s approach is: Why not use a comic book for that? A fun and entertaining way to explain the basics of machine learning in fairly simple words.
Learning Machine Learning


Does anyone actually know what Natural Language Processing is? I didn’t. Currently I’m reading up on it a little and during my research I found this article that made the whole subject immediately more tangible for me:
What is Natural Language Processing?

Links, links, links!

If you are now looking for a substantial link list on AI with blogs, websites, companies, tools and a list of people you should follow on Twitter, you will definitely find it here.
The Non-Technical Guide to Machine Learning & Artificial Intelligence
(similar title as above, but with a different approach)

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