Did you know that 10% of your data contains 90% of the value? This means that most organizations are leaving money on the table: they could get to value from their data stack ten times faster.
Don’t wait to design an application that uses your data until all the data is cleansed, migrated, and processed. Because designing an initial model or baseline machine learning system can provide critical cost- ad time-saving intelligence.
I can help. I’m a five-star rated machine learning engineer (see some testimonials below). I invented the fields of inductive transfer and decision intelligence. My CV is here. I write regularly about machine learning topics.
What I can do for you
I build and integrate machine learning systems, and I’m passionate about demystifying this technology and making it accessible so that machine learning can be used throughout your organization to drive competitive advantage.
My work includes tasks like connecting data between S3 and Mahout / EMR, running regressions in R or H2O, designing learning visualizations, designing success measurement code, finding the right number of hidden units in a neural network, and designing a machine learning solution to provide maximum value to your company, as soon as possible. I am a coder, can manage a team of analysts, train your staff, and present to your executives.
Over the years, I’ve built thousands of machine learning systems: neural networks, decision trees, regression systems, and more, in areas like hazardous waste management, forensic hair analysis, computer vision, and DNA pattern recognition for the Human Genome Project.
I speak the language of business as well as “machine learning”-ese. I’ll work with you on a focused project to get your needs met, and we’ll do it in record time and with minimal impact to your people and systems.
Working with my team at Quantellia, we also go deeper into the data stack, providing data management, robust high-performance enterprise-grade survey systems, and our award-winning World Modeler™ software with data binding to many sources.