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William Vorhies's Blog (273)

From Optimization to Prescriptive Analytics

Summary:  True prescriptive analytics requires the use of real optimization techniques that very few applications actually use.  Here’s a refresher on optimization with examples of where and how they’re best used.

 

Predictive analytics and optimization have gone hand in hand since the very beginning.  But in…

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Added by William Vorhies on February 18, 2019 at 10:01am — 1 Comment

Capturing the Value of ML/AI – the Challenge of Offensive versus Defensive Data Strategies

Summary:  A major pain point is standing in the way of many companies’ ability to maximize the value of their ML/AI initiatives.  The competing goals of data flexibility versus single version of the truth can only be solved with an effective data governance strategy.

 

There are many reasons why companies…

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Added by William Vorhies on February 11, 2019 at 10:15am — No Comments

Advanced Analytic Platforms – Incumbents Fall – Challengers Rise

This article is currently under revision.

Added by William Vorhies on February 4, 2019 at 9:30am — 2 Comments

One Shot Learning and Other Strategies for Reducing Training Data

Summary: Not enough labeled training data is a huge barrier to getting at the equally large benefits that could be had from deep learning applications.  Here are five strategies for getting around the data problem including the latest in One Shot Learning.

 

For at least the last two years we’ve been in an…

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Added by William Vorhies on January 28, 2019 at 9:56am — 1 Comment

Doctors are from Venus, Data Scientists from Mars – or Why AI/ML is Moving so Slowly in Healthcare

Summary: The world of healthcare may look like the most fertile field for AI/ML apps but in practice it’s fraught with barriers.  These range from cultural differences, to the failure of developers to really understand the environment they are trying to enhance, to regulatory and logical Catch 22s that work against adoption.  Part 3 of 3.

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Added by William Vorhies on January 21, 2019 at 7:59am — 2 Comments

The AI/ML Opportunity Landscape in Healthcare. Do It Right or It Will be More of a Mine Field.

Summary:  Despite hundreds of projects and thousands of data scientists devoted to bringing AI/ML to healthcare, adoption remains low and slow.  A good portion of this problem is our own fault for failing to see the processes being disrupted through the eyes of the physician users.  Here we lay out the healthcare opportunity landscape but for data scientists following classical disruption strategies, it may be more of a minefield.  Part 2 of…

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Added by William Vorhies on January 14, 2019 at 8:00am — No Comments

Seeing the AI/ML Future in Healthcare Through the Eyes of Physicians. It Doesn’t Look Quite the Way Data Scientists See It.

Summary: If you want to understand the promise of AI/ML in healthcare you need to see it through the eyes of physicians, the ultimate users.  Turns out these folks aren’t the rapid adopters you’d think they’d be and the problem is largely with the way data scientists have tried to implement.  Part 1 of 3.

 

It’s…

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Added by William Vorhies on January 7, 2019 at 8:00am — 4 Comments

5 Predictions about Data Science, Machine Learning, and AI for 2019

Summary:  Here are our 5 predictions for data science, machine learning, and AI for 2019.  We also take a look back at last year’s predictions to see how we did.

 

It’s that time of year again when we do a look back in order to offer a look forward.  What trends will speed up, what things will actually happen,…

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Added by William Vorhies on December 17, 2018 at 8:50am — No Comments

Who Do We Blame When an AI Finally Kills Somebody

Summary:  We’re rapidly approaching the point where AI will be so pervasive that it’s inevitable that someone will be injured or killed.  If you thought this was covered by simple product defect warranties it’s not at all that clear.  Here’s what we need to start thinking about.

 

So far the press…

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Added by William Vorhies on December 10, 2018 at 10:07am — 1 Comment

Can AI Make B2B Sales Better?

Summary: Sales is supposed to be an area that is more immune to replacement by AI than many others because of the high level of impromptu and improvisational human contact required.  That remains true.  But AI is showing that it can be a valuable augment to B2B sales and some early adopters are scoring big gains.

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Added by William Vorhies on December 4, 2018 at 9:59am — No Comments

The Two (Conflicting) Definitions of AI

Summary:  There are two definitions currently in use for AI, the popular definition and the data science definition and they conflict in fundamental ways.  If you’re going to explain or recommend AI to a non-data scientist, it’s important to understand the difference.

 

For a profession as concerned with accuracy as we are, we do a really poor job at naming things, or at least being consistent in the naming.  “Big Data” – totally misleading…

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Added by William Vorhies on November 27, 2018 at 8:23am — No Comments

Things that Aren’t Working in Deep Learning

Summary:  This may be the golden age of deep learning but a lot can be learned by looking at where deep neural nets aren’t working yet.  This can be a guide to calming the hype.  It can also be a roadmap to future opportunities once these barriers are behind us.

 

We are living in the golden age of deep…

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Added by William Vorhies on November 18, 2018 at 11:14am — No Comments

The Best Opportunities in AI for Data Scientists

Summary:  Looking for your next job in an early stage company but want to make sure your startup has staying power.  Follow the expert rankings by CB Insights that also show us the changing trends in how AI startups should be focusing their offerings.

 

Let’s suppose…

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Added by William Vorhies on November 5, 2018 at 4:18pm — No Comments

Digital Decisioning Platforms – A New Way to Slice the Pie

Summary:  Digital Decisioning Platforms is a new segment identified by Forrester that marries Business Process Automation, Business Rules Management, and Advanced Analytics.  For platform developers it’s a new way to slice the market.  For users it eases integration of predictive models into the production environment.

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Added by William Vorhies on October 30, 2018 at 8:30am — No Comments

The Case for Just Getting Your Feet Wet with AI

Summary:  Even if you’re not big enough to have a full blown data science group that shouldn’t hold you back from benefiting from AI.  The market has evolved so that there are now industry and process specific vertical applications available from 3rd party AI vendors that you can implement.  There are just a few things to look out for.

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Added by William Vorhies on October 23, 2018 at 7:30am — No Comments

Advanced Analytics – The Fourth Great Lever of Corporate Change

Summary:  Advanced analytics and AI are the fourth great lever available to create organic improvement in corporations.  We’ll describe why this one is different from the first three and why the CEO needs the direct help of data scientists to make this happen.

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Added by William Vorhies on October 15, 2018 at 2:33pm — 2 Comments

Practicing ‘No Code’ Data Science

Summary:  We are entering a new phase in the practice of data science, the ‘Code-Free’ era.  Like all major changes this one has not sprung fully grown but the movement is now large enough that its momentum is clear.  Here’s what you need to know.

 

We are…

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Added by William Vorhies on October 9, 2018 at 9:54am — 3 Comments

Lots of Free Open Source Datasets to Make Your AI Better

Summary:  There are several approaches to reducing the cost of training data for AI, one of which is to get it for free.  Here are some excellent sources.

 

Recently we wrote that training data (not just data in general) is the new oil.  It’s the difficulty…

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Added by William Vorhies on October 2, 2018 at 7:23am — No Comments

What’s New in Data Prep

Summary:  If you’re still writing code to clean and prep your data you're missing big opportunities for efficiency and consistency with modern data prep platforms.

 

Two things are true. 

  • Data prep still occupies about 80% of our model building time – the…
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Added by William Vorhies on September 24, 2018 at 11:00am — 3 Comments

The Fourth Way to Practice Data Science – Purpose Built Analytic Modules

Summary:  Purpose Built Analytic Modules (PBAMs) such as those for Fraud Detection represent a fourth way to practice data science, a new model for the good use of Citizen Data Scientists, and a new market for AI-first companies.

 

It appears that data science has exited…

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Added by William Vorhies on September 18, 2018 at 9:07am — No Comments

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