machine learning

Are LLMs a simple solution? And if so, for what problems?

Sep 14, 2023 · 5 min read · llms simplicity machine learning product ·

The other day, I was reading a post by Venkatash Rao (thousands of words of under-edited brilliance, as usual), and was struck by this note about the complexity of climate solutions: I tend to take as an article of faith the systems science rule of thumb that the complexity of solutions generally matches the complexity …

A Critique of The Markup’s Investigation into Predictive Models of Student Success

May 29, 2023 · 8 min read · machine learning journalism predictive ·

Share on:

Recently, tech-journalism site The Markup ran a long, detailed, critical investigation of a predictive machine learning model used by the State of Wisconsin to identify public school students at risk of not graduating. I mostly agree with the conclusions of the piece -- the system appears not to be fit for purpose and …

New Publications and Upcoming Talks

Sep 4, 2018 · 1 min read · algorithms conferences data science machine learning meetup software architecture ·

Share on:

Just a quick post here to note a few professional accomplishments: I just added a new publication to my vita -- a peer-reviewed conference proceeedings article about abstractions for building repeated, related versions of similar predictive models. Check out some longer thoughts on Medium, or read the full article. …

A few things I learned from two small Data Science conferences

Jul 16, 2017 · 5 min read · data science machine learning conferences ·

Share on:

This post was originally published on Medium I recently attended two small conferences — the ISBIS (International Society for Business and Industrial Statistics) 2017 conference, held at IBM Research in Westchester County, and the Domino Data Lab Popup, held in West SoHo. I was invited to speak at ISBIS (slides here, …

What do Data Scientists mean by “Scaling”?

Jun 9, 2017 · 7 min read · machine learning data science scaling software architecture ·

Share on:

This post was originally published on Medium Occasionally when chatting with other data scientists, especially with others who are interested in integrating predictive models into production software system, the word “scaling” comes up. Not this. Although some West Coast data scientists are into this kind of scaling …

Transparency, Trust, and Proprietary Predictive Analytics

Feb 27, 2017 · 9 min read · data science machine learning algorithms ethics ·

Share on:

This post was originally published on Medium A particularly good talk at Strata NY last year was by Brett Goldstein, former CIO of Chicago, who talked about accountability and transparency in predictive models that affect people’s lives. This struck a strong chord with me, so I wanted to take some time to write down …

Insights from a Predictive Model Pipeline Abstraction

Nov 7, 2016 · 5 min read · data science machine learning software engineering software architecture programming ·

Share on:

This post was originally published on Medium When building a complex system, it’s often helpful to think about the design of that system using patterns and abstractions. Architects and software engineers do so frequently, and the experience of implementing predictive modeling pipelines has recently led to a variety of …

Patterns for Connecting Predictive Models to Software Products

Jul 12, 2016 · 9 min read · machine learning data science software engineering R ·

Share on:

This post was originally published on Medium You’re a data scientist, and you’ve got a predictive model — great work! Now what? In many cases, you need to hook it up to some sort of large, complex software product so that users can get access to the predictions. Think of LinkedIn’s People You May Know, which mines your …