Resolving Confusions: AI, Machine Learning, and Deep Learning

SAS recently produced a helpful video to cut through the misunderstandings that have developed in the market concerning the distinctions between AI, machine learning, and deep learning (many marketers using the terms interchangeably)

In summary:
> AI is a term for a solution which often utilizes machine learning as a component method to emulate human decision making
> Machine learning is not AI, rather it represents a broad set of methods which often support AI solutions
> Machine learning encompasses a large set of algorithmic statistical techniques for pattern extraction and decision making from data
> Deep learning is a family of machine learning techniques which support learning from data representations, deep neural networks being a popular example
> Deep learning has produced efficacious results especially in the areas of image and speech recognition, hence its frequent use as a component in AI solutions
> Deep learning is not always the best machine learning technique – a champion-challenger approach should be applied to test many ML techniques
> Deep learning techniques do not absolve implementers from the need to treat and understand the data they feed into the algorithm – garbage in-garbage out
> Machine learning correlation does not equal causation: ignoring explanatory theory when developing and testing algorithms often leads to overfitting and misunderstandings between what the implementer intends versus what the algorithm produces – see Science ‘The Parable of Google Flu Trends’

Click to access The%20Parable%20of%20Google%20Flu%20(WP-Final).pdf

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About SARK7

Scott Allen Mongeau (@SARK7), an INFORMS Certified Analytics Professional (CAP), is a researcher, lecturer, and consulting Data Scientist. Scott has over 30 years of project-focused experience in data analytics across a range of industries, including IT, biotech, pharma, materials, insurance, law enforcement, financial services, and start-ups. Scott is a part-time lecturer and PhD (abd) researcher at Nyenrode Business University on the topic of data science. He holds a Global Executive MBA (OneMBA) and Masters in Financial Management from Erasmus Rotterdam School of Management (RSM). He has a Certificate in Finance from University of California at Berkeley Extension, a MA in Communication from the University of Texas at Austin, and a Graduate Degree (GD) in Applied Information Systems Management from the Royal Melbourne Institute of Technology (RMIT). He holds a BPhil from Miami University of Ohio. Having lived and worked in a number of countries, Scott is a dual American and Dutch citizen. He may be contacted at: LinkedIn: Twitter: @sark7 Blog: Web: All posts are copyright © 2020 SARK7 All external materials utilized imply no ownership rights and are presented purely for educational purposes.

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