Non-traditional strategies for mid-career switch to Data Science and AI
In this post, I explore strategies to switch to Data Science mid-career. This switch is not easy, but based on the experience of many who I have taught/mentored/recruited – it is possible. Most people consider PhD/MooC etc for switching their career to Data Science. But here, I will explore some non-traditional/unorthodox ways of switching to Data Science. Click here to read more.
Have You Heard About Unsupervised Decision Trees
Unless you’re involved in anomaly detection you may never have heard of Unsupervised Decision Trees. It’s a very interesting approach to decision trees that on the surface doesn’t sound possible but in practice is the backbone of modern intrusion detection. Click here to read more.
Reflective Random Walks with Applications in Fintech
This is the kind of mathematics used by Wall Street quants and in operations research. Hopefully my presentation here is much less arcane than the traditional literature on the subject, and accessible to a much broader audience, even though it features the complex equations characterizing such a process. Click here to read more.
Upcoming webinar -- Data Literacy: Bridging the Gap. Register here.