Machine Learning Times
EXCLUSIVE HIGHLIGHTS
You Must Address These 4 Concerns To Deploy Predictive AI
 Originally published in Forbes Most predictive AI projects fail to launch into production. The...
Hybrid AI: Industry Event Signals Emerging Hot Trend
 Originally published in Forbes After decades chairing and keynoting myriad...
Predictive AI Thrives, Despite GenAI Stealing The Spotlight
 Originally published in Forbes Generative AI and predictive AI ought...
For Managing Business Uncertainty, Predictive AI Eclipses GenAI
  Originally published in Forbes The future is the ultimate...

Author Archive

What Happened to Hadoop? And Where Do We Go from Here?

 Originally published by InsideBigData, September 4, 2019. Apache Hadoop emerged on the IT scene in 2006 with the promise to provide organizations with the capability to store an unprecedented volume of data using cheap, commodity hardware. In a sense, Hadoop helped usher in the era of big data.  Hopes were high and expectations were higher.

Some Thoughts On Being a Data Science Entrepreneur in a Disruptive Economy

 The movie “Being There” may seem like an odd theme on an article concerning data science entrepreneurship. Yet, this movie highlights certain characteristics which are essential to success as an entrepreneur within all disciplines including data science....

Asking the Right Analytics Questions and Whether Tiger Woods is better than Jack Nicklaus

  One of the most fundamental contributions we can make as consultants is to help our clients ask the right questions of their data. We’re often asked to help solve problems that turn out to be too...

The Death of Big Data and the Emergence of the Multi-Cloud Era

 Originally published in KDnuggets, July, 2019 The Era of Big Data is coming to an end as the focus shifts from how we collect data to processing that data in real-time. Big Data is now a business...

12 Things I Learned During My First Year as a Machine Learning Engineer

 Originally published in Towards Data Science, July 6, 2019 Being your own biggest sceptic, the value in trying things which might not work and why communication problems are harder than technical problems. Machine learning and data science...

From Foodie Pic to Your Plate: Generating Recipes With Facebook AI

  Originally published in Synced, June 20, 2019 Imagine snapping a pic of your tasty restaurant entree or the magnificent lasagna in a foodie post, and up pops a recipe for said dish. Facebook AI has now...

How Pattern Recognition and Machine Learning Helps Public Safety Departments

 Originally published in StateTechMagazine, May, 2019 For today’s leading deep learning methods and technology, attend the conference and training workshops at Data Driven Government (formerly PAW Government), September 25, 2019, in Washington, DC.  The NYPD is leading...

Key Considerations in Applying Deep Learning to Predict Consumer Behavior

 The development and application of predictive analytics solutions for organizations is not new, particularly in the area of consumer behavior. Models have been built since the end of the Second World War to predict consumer behavior with...

19 Inspiring Women in AI, Big Data, Data Science, Machine Learning

 Originally published in KDnuggets, March 2019. For today’s leading deep learning methods and technology, attend the conference and training workshops at Deep Learning World Las Vegas, June 16-20, 2019.   In honor of International Women’s Day on March 8,...

How Federated Learning Could Shape the Future of AI in a Privacy-Obsessed World

 Originally published in VentureBeat, June 3, 2019 For today’s leading deep learning methods and technology, attend the conference and training workshops at Deep Learning World, June 16-19, 2019 in Las Vegas.  You may not have noticed, but...

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