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Published on April 25th, 2019 | by Emergent Enterprise

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How to Apply Machine Learning to Business Problems

Emergent Insight:

Artificial intelligence can sometimes seem to be the answer to every business challenge or problem. But what does actual adoption look like? Daniel Faggella at emerj.com shares some real world applications of machine learning and how it is being used by businesses globally. Got clean, labelled data? That’s a good start!

Original Article:

It’s easy to see the massive rise in popularity for venture investment, conferences, and business-related queries for “machine learning” since 2012 – but most technology executives often have trouble identifying where their business might actually apply machine learning (ML) to business problems.

With new AI buzzwords being created weekly, it can seem difficult to get ahold of what applications are viable, and which are hype, hyperbole or hoax.

In this article, we’ll break down categories of business problems that are commonly handled by ML, and we’ll also provide actionable advice to begin a ML initiative with the right approach and perspective (even it’s the first such project you’ve undertaken at your company).

Best of all, we’ll reference real business use cases, along with quotes and perspectives about “how to solve business problems with ML” from our network of AI researchers and executives. By the end of this article, you’ll have a good idea as to whether any of your present business challenges might be handled well with ML.

What Kinds of Business Problems Can Machine Learning Handle

1 – Is the prediction you’re trying to make (or decision you’re trying to make) complex enough to warrant ML in the first place?

If it’s possible to structure a set of rules or “if-then scenarios” to handle your problem entirely, then there may be no need for ML at all. Also, if there is no precedent for any successful outcome applying machine learning to the specific problem to which you’re developing, it may not be the best foray into the ML world.

For illustrative purposes, it will be helpful to list a number of well-established business use-cases for machine learning so that you (the reader) can churn up your own application ideas:

  • Face detection: It’s incredibly difficult to write a set of “rules” to allow machines to detect faces (consider all the different skin colors, angles of view, hair / facial hair, etc), but an algorithm can be trained to detect faces, like those used at Facebook. Many tools for facial detection and recognition are open source. Below is a video of facial recognition using MATLAB:

To continue reading and see video, go here…

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Emergent Enterprise

The Emergent Enterprise (EE) website brings together current and important news in enterprise mobility and the latest in innovative technologies in the business world. The articles are hand selected by Emergent Enterprise and not the result of automated electronic aggregating. The site is designed to be a one-stop shop for anyone who has an ongoing interest in how technology is changing how the world does business and how it affects the workforce from the shop floor to the top floor. EE encourages visitor contributions and participation through comments, social media activity and ratings.



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