Crossing A Finish Line

Finishing the Cornell Machine Learning Certificate

I recently completed the Cornell University Machine Learning Certificate program.

Pomp and Circumstance and All That Jazz

Coincidentally, at the same time I was completing the last course in this certificate program, at work I was also steeped in some intensive AI/ML training for Google Cloud SMEs. The cherry on top was I was (am) smack dab in the middle of my summer Inferential Modeling class as part of the Master’s program in Health Data Science. To say last week was a little… intense… would be an understatement. And while I’m very happy to be on this side of things, it has taken me about a week to emotionally recover.

Over the course of the last few weeks, I have written stub starts of several blog posts that I have every intention of circling back to when time and energy permit. The highlights:

Inference vs. Inferential Modeling: Clearing up some terminology issues for Machine Learning, and explaining the place of inferential modeling in the field. It’s not all about predicting the future!

Explainable Explainability: Detailing the challenges in explaining the effect of inputs to non-linear regression models and why it is absolutely critical that we do so, plus some of the modern approaches being explored today. Knowing when neural networks are cheating rather than actually learning…

When Getting It Right Gets It Wrong: Understanding the role of intentionally introducing sloppiness (“regularization”) into ML models, the approaches taken, and why they work even though it seems counter-intuitive. Fascinated by stochastic gradient descent, but covering some other common methods as well.

Serverless Data Science: A preview of Google’s new Vertex AI platform and how it brings the power of Google Cloud data science tools even closer to the masses. Plus, some late-breaking news for BigQuery ML!

The problem I’m going to have is that since creating those stubs, I’ve come across another half dozen or so interesting learnings that I want to dive into, and I still haven’t had a chance to circle back to the topics in my last drive-by post either. If having too many cool things to write about is a rich person’s problem, I am among the wealthiest of the wealthy.

Data Science, Big Data, & Cloud nerd with a focus on healthcare & a passion for making complex topics easier to understand. All thoughts are mine & mine alone.