Accuracy and Trust in Machine Learning

A few weeks ago, I wrote about machine learning risks where I described four ‘buckets’ of risk that needed to be understood and mitigated when you have machine learning initiatives.  One major risk that I *should* have mentioned explicitly is the risk of accuracy and trust in machine learning.  While I tend to throw this […]

Machine learning risks are real. Do you know what they are? 

Machine Learning Risks are real and can be very dangerous if not managed / mitigated. Everyone wants to ‘do’ machine learning and lots of people are talking about it, blogging about it and selling services and products to help with it. I get it…machine learning can bring a lot of value to an organization – […]

What can you DO with Machine Learning?

Everyone’s talking about machine learning (ML) and Artificial Intelligence (AI) these days.  If you are a CxO or work in IT or marketing, I’d bet that you hear these terms more than you probably want to. It feels an awful lot like the early data of Big Data or Business Intelligence or the days when […]

Are your machine learning models good enough?

Imagine you’re the CEO of XYZ Widget company.  Your Chief Marketing Officer (CMO),  Chief Data Officer (CDO) and Chief Operations Officer (COO) just finished their quarterly presentations and were highlighting the success from the various machine learning projects that have been in the works. After the presentations were complete, you begin to wonder – ‘are […]

Deep learning – when should it be used?

“When should I use deep learning?” I get asked that question constantly. The answer to this question is both complicated and simplistic at the same time. The answer I usually give us something along the lines of ‘if you a lot of data and an interesting / challenging problem, then you should try out deep […]