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Text Mining & Analysis
In the recently published Forbes Tech Council article, “Just when A Data Scientist Has It All Figured Out, The Rules Change,” I had the opportunity to discuss the evolution of Artificial Intelligence and the future prospects for rising data scientists.
In the article, I presented some statistics from The Bureau of Labor Statistics that reinforces…
I recently had the privilege of presenting AI as the cornerstone of digital transformation to the College of Certified Public Accountants, Puerto Rico. The accounting and finance industries have changed drastically in the past few years, and are embracing digital transformation, most notably AI, like never before. Today, public accountants are using AI for accounting…
I recently explored the changing requirements of today’s data scientists in a Forbes Technology Council article. While it traditionally has not been the focus, today, soft skills are just as important as technical prowess.
Since AI deals with real-world problems impacting people, communication skills and empathy are the traits that companies want to see in…
Imagine entering a movie theater to watch the latest blockbuster. As soon as it’s over, another movie immediately begins and hooks you from the start. Once that one is over, a voice-over directs you to the film playing one door down, where another intriguing movie is about to begin. Before you know it, you’ve spent…
New applications of machine learning in insurance make headlines every week. Following are trending AI solutions that are transforming insurance in auto, home, and healthcare markets.
Anticipating versus Controlling Decisions
AI-based predictive analytics is gaining steam across industries, helping insurance firms predict customer churn; retailers predict customer preferences; or physicians anticipate the patients that will be making a return visit. It’s becoming quite popular and helping firms root out problems even before they occur; but the problem, is, prescriptive AI has…
To get the best results out of AI projects, teams should follow an agile data science process, a hybrid approach that blends techniques from the scientific method, design thinking methodologies and agile software development framework.
When working on artificial intelligence models, you may feel like you are standing on the shoulders of giants. Improve machine learning models is one of the most challenging tasks for a data scientist and it requires a lot of experimentation and testing. Different optimization techniques can be applied to different types of models. For example,…
The benefits of AI are becoming well-established when applied to the right applications, but why do they sometimes fail to deliver on the promise? This was a question I examined in a recent article I wrote for the Forbes Technology Council.
Below are a few of the missteps I shared:
Gathering the wrong or incomplete…