Summary: Over the last eight years predictive analytics has become a fully mature technology with wide adoption among the largest and most successful companies. The Advanced Analytic Platforms we have to make our work more effective and efficient also show substantial improvement.
Summary: If you are mid-career and thinking about switching into data science here are some things to think about in planning your journey.
We get lots of inquiries from readers asking for career advice and many of these identify as mid-career looking to switch into data science. If you’re in this group you face some of the same challenges beginners do but also some that are unique to your circumstance. Here are some thoughts and observations that may…Continue
Summary: As your data lake grows larger and your user group more diverse you will need these tools that automatically catalog data and control access to your information. They are a huge benefit and only enhance the spirit of free exploration of data for new value.
Added by William Vorhies on September 26, 2017 at 9:32am — No Comments
Summary: In just the last 10 months based only on facial characteristics deep learning has been used to predict who is a criminal and who is gay. These are rigorous, peer reviewed studies published in academic journals. How should this knowledge be used and how will the public react?
Summary: With only slight tongue in cheek about the road ahead we report on the just passed House of Representative’s new “Federal Automated Vehicle Policy” as well as similar policy just emerging in Germany. As a model of regulation on emerging AI technology we think they got this just about right.
Added by William Vorhies on September 12, 2017 at 9:35am — No Comments
Summary: Dealing with imbalanced datasets is an everyday problem. SMOTE, Synthetic Minority Oversampling TEchnique and its variants are techniques for solving this problem through oversampling that have recently become a very popular way to improve model performance.
Summary: In the first part of this series we described the basics of Reinforcement Learning (RL). In this article we describe how deep learning is augmenting RL and a variety of challenges and considerations that need to be addressed in each implementation.
Added by William Vorhies on August 29, 2017 at 9:03am — No Comments
Summary: Reinforcement Learning (RL) is likely to be the next big push in artificial intelligence. It’s the core technique for robotics, smart IoT, game play, and many other emerging areas. But the concept of modeling in RL is very different from our statistical techniques and deep learning. In this two part series we’ll take a look at the basics of RL models, how they’re built and used. In the next part, we’ll address some of the complexities that make development a…Continue
Added by William Vorhies on August 22, 2017 at 9:00am — No Comments
Summary: Recently we’ve been profiling Automated Machine Learning (AML) platforms, both of the professional variety, and particularly those proprietary one-click-to-model variety that are being pitched to untrained analysts and line-of-business managers. Since our first article, readers have suggested some additional companies we should look at which are profiled here along with some interesting observations about who is buying and why.
Summary: There are a variety of new Automated Machine Learning (AML) platforms emerging that led us recently to ask if we’d be automated and unemployed any time soon. In this article we’ll cover the “Professional AML tools”. They require that you be fluent in R or Python which means that Citizen Data Scientists won’t be using them. They also significantly enhance productivity and reduce the redundant and tedious work that’s part of model…Continue
Added by William Vorhies on July 25, 2017 at 1:36pm — No Comments
Summary: A year ago we wrote about the emergence of fully automated predictive analytic platforms including some with true One-Click Data-In Model-Out capability. We revisited the five contenders from last year with one new addition and found the automation movement continues to move forward. We also observed some players from last year have now gone in different directions. …Continue
Summary: You’d think that the internet was the core of the digital economy but it’s not. Data science is the core without which the digital economy wouldn’t exist and increasingly it’s AI that’s moving the needle in consumer engagement.
Added by William Vorhies on July 11, 2017 at 6:46am — No Comments
Summary: Is everyone a ‘data scientist’? What about ‘data engineers’ and the junior versus senior, or skill level distinctions? We do seem to need some agreement about titling. Data Scientists is still the prestige title but there are some folks lobbying to take that title away.
Summary: The drive toward transparency and explainability in our modeling seems unstoppable. Up to now that meant sacrificing accuracy for interpretability. However, the ensemble method known as RuleFit may be the answer with both explainability and accuracy meeting or exceeding Random Forest.
If you’re like me and not doing modeling in a highly regulated industry like mortgage finance or insurance then when you produce a model, you are…Continue
Added by William Vorhies on June 27, 2017 at 10:02am — No Comments
Summary: There’s a three way technology race to bring faster, easier, cheaper, and smarter AI. High Performance Computing is available today but so are new commercial versions of actual Quantum computers and Neuromorphic Spiking Neural Nets. These two new entrants are going to revolutionize AI and deep learning starting now.
Summary: Quantum computing is already being used in deep learning and promises dramatic reductions in processing time and resource utilization to train even the most complex models. Here are a few things you need to know.
Added by William Vorhies on June 13, 2017 at 8:00am — No Comments
Summary: This is the second in our multi-part series on Quantum computing. In this article we’ll dive a little deeper into what’s available, what’s coming soon, and some considerations for getting in early.
In the first article in this series, “…Continue
Summary: Quantum computing is now a commercial reality. Here’s the story of the companies that are currently using it in operations and how this will soon disrupt artificial intelligence and deep learning.
Summary: This is a lesson in how it may be possible to snatch victory from the jaws of defeat. 1.) A good ROC score does not necessarily mean a good model. 2.) Even a weak model may be good at the top and bottom – consider how you can use that.
This is a lesson in how it may be possible to snatch victory from the jaws of defeat. In our world, defeat is ending up with a poor model that doesn’t do what you’d hoped. This story about a particular project…Continue
Added by William Vorhies on May 23, 2017 at 5:55am — No Comments
Summary: Someone had to say it. In my opinion R is not the best way to learn data science and not the best way to practice it either. More and more large employers agree.