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Deep Learning Use Cases: What can deep learning do for businesses?

Next year, spending on machine learning is expected to hit $12.5 billion.  $8 billion of that will be spent on business services and machine learning applications.  Deep learning algorithms are on the leading edge of that spending wave.  3 years ago, most businesses were getting up to speed with data science. ...

RI3P: A Mature Structure For Machine Learning Success

I’ve been teaching businesses about RI3P for the last 4 years.  It’s a structure that works to discover machine learning concepts and turn them into revenue generating products.  Without a strategy and structure around machine learning, it will not succeed.  That’s true in startups or Fortune 100 companies. ...

Machine Learning At The Tipping Point: Why Is Now The Time For Businesses To Act?

Machine learning is the driver and enabling technology for several emerging technologies.  Machine learning is a back-end technology for a front end consisting of augmented reality, virtual reality, chatbots, digital assistants, sensors, data visualizations, prescriptive analytics, and many others.  It’s the...

Machine Learning At The Tipping Point: How To Get Enterprises To Buy In

At IBM Connect I saw a company faced with a challenge common to many software vendors and to machine learning as a whole. Get customers who are deeply rooted in the old software model to join them in moving towards this new era of machine learning solutions. From startups to established players, the push into...

How To Stay Competitive In An Evolving Machine Learning Landscape

While the majority of businesses are just getting their feet wet in the machine learning space, many are already reaping the benefits. The technology is moving forward rapidly. Getting left behind is a big concern for the early adopters and a driver for fast followers.Staying competitive in a rapidly moving,...

What The C-Suite Needs To Know About Data Science

You need to be involved. While 75% of companies are planning to invest in big data over the next two years, the number that will see the kinds of returns they are expecting is much lower. There are a number of factors that lead to success with analytics, but without you none of those really matter.Many executives get...

Hated The Presidential Debate? Machine Learning Is Coming To The Rescue

All I could think about during the debate was, ‘This will look so different in 2020.’ For me, the debate was framed by a talk I gave last week about where machine learning goes next.  The internet of things (IoT) will be the data source. Real time processing will be the facilitator. Machine learning driven...

Getting Data Science On The Same Page With Marketing: Perception Vs. Utility Metrics

There are few groups who need each other more than data science and marketing. However, the communication between the two is a lot harder than it sounds because they understand the business from two different perspectives. Metrics are an area where the two often meet and clash because data scientists are focused on...

How To Keep Complexity Out Of Machine Learning Products

I hear a lot of complaints about machine learning from business clients. It’s too complicated is one of them. Machine learning is complex by nature. The more that complexity spills over to users and executive management, the more turned off to machine learning they become. I’ve seen it happen in real...

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