Category: IBM
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IBM THINK 2022 Champions Roundtable
At this year’s IBM THINK, I had the pleasure of joining fellow IBM Champions Jason Juliano, Steven Perva, and Craig Mullins along with IBMs Luke Schantz, JJ Asghar, Elizabeth Joseph, and the legendary Gabriela de Quieroz for a wide-ranging discussion on AI, data, bias, quantum computing, genomics, and more. Give a watch/listen! Can’t see anything?…
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Building Trusted AI Systems: A Fireside Chat with IBM
I recently had the opportunity to sit down with Lauren Frazier from IBM to discuss how we go about building trusted AI systems in a fireside chat livestream. We covered a ton of ground. Can’t see anything? Watch it on YouTube here. What is Fair? Fairness is a difficult subject to tackle, because people have…
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IBM Watson AutoAI Time Series Forecasting Bakeoff
Today, let’s take a look at a new offering from IBM, the new AutoAI Time Series Forecasting module. Before we begin, let’s define a few things. What is Time Series Forecasting? Time series forecasting is predicting one or more data variables over some future time, based on previous data. Why is Time Series Forecasting Valuable?…
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GRAMMY Debates with IBM Watson
This week, I had the pleasure of sitting down with IBM Project Debater system lead Yoav Katz for an in-depth chat about how Project Debater has evolved since its debut at IBM THINK 2019 and how it’s being used for the GRAMMY Debates with Watson. What is IBM Project Debater For those unfamiliar, Project Debater…
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Learning Data Science Techniques With IBM Watson Studio Modeler
When it comes to learning data science, one of the challenges we face is just how seemingly daunting the field is to learn. There are so many techniques, tactics, and strategies that it’s difficult to know where to start. Learning something new always begins with an understanding of the basics. From martial arts to dance…
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IBM THINK 2020 Digital Experience: Day 2 Review
Day 2 of THINK 2020 was much more meat and potatoes, from use cases for AI to process automation. Rob Thomas, SVP Cloud and Data, showed a fun stat that early adopters of AI reaped a 165% increase in revenue and profitability, which was nice affirmation. But the big concept, the big takeaway, was on…
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IBM THINK 2020 Digital Experience: Day 1 Review
We look back at day 1 of the IBM THINK Digital Experience. Completely different from the in-person experience, but neither better nor worse. Highlights: – AI for IT – complexity of systems – Rob Thomas on a more layperson-friendly Watson Studio AutoAI – Tackling of more complex issues with AI – Data supply chain and…
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You Ask, I Answer: Data Science Tools for Marketers?
Monina asks, “What tools are useful to help marketers dig deep into their organization’s data?” The answer to this question depends on the level of skill a marketer has in data science, specifically the technical and statistical skillsets. I’d put the available tools in categories of beginner, intermediate, and advanced. Beginner tools help marketers extract…
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You Ask, I Answer: Multi-Objective Optimization for IBM Watson Studio AutoAI?
Arjuna asks, “Could you please suggest an approach to forecast multiple targets (e.g., is there a way to select multiple columns in AutoAI). In our use case, we need to develop time series forecasts for multiple products. If we correctly understood AutoAI, it will allow us to select one column at a time to generate…
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You Ask, I Answer: RFM Analysis for Small Business with Google Sheets and IBM Watson Studio
CC asks, “What’s the most valuable analysis overall for a small business to perform?” If we define a small business as an enterprise with less than $1 million in sales and fewer than 10 employees, then from an overall business perspective it’s got to be RFM analysis. Nothing else comes close in terms of helping…