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AI, ML, NN and DL: a visual explanation

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There appears to be a lot of confusion between the terms Artificial Intelligence (AI), Machine Learning (ML), Neural Networks (NN) and Deep Learning (DL).  Based on research from various popular blogs and articles, here is my attempt at a simple visual explanation:

The Research Process

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To answer interesting questions, you need data. You begin with an observation that you want to understand including anecdotal observations.  For example, a certain website layout attracts more visitors to our web page than a different website layout.  From your observations, you generate explanations or theories of those observations, from which you can make predictions or hypothesis.  To test your hypothesis or predictions, you need data. So you collect relevant data (and to do that you need to identify things that can be measured) and then you analyze those data.  The analysis of your data may support your theory or give you cause to modify the theory. As such, the processes of data collection and analysis and generating theories are intrinsically linked: theories lead to data collection / analysis and data collection / analysis informs theories.  The research process is summarized below: (adapted from Discovering Statistics using R by Andy Field e...

Operationalize Trusted AI with IBM Watson OpenScale

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Satellite imagery and remote sensing puzzles

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If you are looking for a fun way to experience satellite imagery and learn more about remote sensing, check out Earth Image Puzzles here . Here is a solved jigsaw puzzle of SouthEastern PA: Enjoy!

The world of languages

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Courtesy of: Visual Capitalist