Join me at November 7th

Robert Dempsey, Speaker, DC

I'm proud and excited to announce that I will be speaking at the conference on November 7th in McLean, VA. I'll be joined by an excellent lineup of speakers including Vicky Fu from Microsoft, Mark McGovern from CA Technologies, and Elizabeth Haubert of OpenSource Connections. It's a full day of machine learning awesome!

My talk is titled Building a Production-Level Machine Learning Pipeline. Here's what it's about: [Read more…]


A Better Way of Learning Machine Learning

Do you find yourself frustrated in your attempts to learn about machine learning? Do you find, like me, that many of the online classes you attend require a masters or PhD to understand, and that the books you read work with data that looks nothing like what you experience in real life?

My philosophy and approach to software engineering is, “keep it simple, make it work, then make it work better”. I use the same approach for learning. And when it came to digging into machine learning, or ML for short, was it simple? Not so much. But it can be with the right framework in place.

Perhaps you want to learn ML because you see that's the direction the technology industry is heading in and you want one of the jobs that the news people tell us will replace hundreds of others. Perhaps you want to learn ML because you would like a new position at your current job or a new job entirely. Perhaps you don't need ML today, but want to be the technology leader that brings it to your organization and creates a metric ton of business value.

I believe I can help you, but you to tell me if you think that's true.

Today I'm happy to announce a new online course for software engineers who want to gain a foundational knowledge of ML, engineers who, like me, subscribe to the philosophy of Keep it Simple and Make it Work™.

“So what Rob?!”, you might say, “There are tons of courses online where I can learn big data things.” And yes there are, but they aren't like this. They won't give you the complete foundation or support you need, or that added ingredient to get you past the finish line.

Visit the Introduction to Data Science course page to find out what I mean >>