Re: [FRIAM] Deep learning training material

The "celebration of the hand" project (coordinated with UNM's Maxwell museum of anthropology) is nearly 15 years defunct now. We made a tiny bit of progress on some LANL small-business-assistance time from an ML researcher, a small bit of seed-funding and matching time on my own part.   The

Re: [FRIAM] Sorting Algorithm? AI? Identifying "types" within data

To my uneducated eye, this seemed like one of Jon’s problems.Sent from my Dumb PhoneOn Jan 7, 2023, at 6:23 AM, Frank Wimberly wrote:This answer seems reasonable to me.  I worked on Project Talent during 1967 which had some similar goals and data. 

Re: [FRIAM] Deep learning training material

Like Python, Lisp is type-checked at runtime. Python does have an optional static type system . It's been a while since I worked with Haskell, but at the time I really appreciated the static typing. It seemed that once I got something to compile, it

Re: [FRIAM] Deep learning training material

Thanks for the references, I've briefly looked at them and am looking forward to perusing them more closely. The interpretation of ML is a big thing of course. The machine gives you the results and it would sometimes be nice if it can be accompanied by some explanation of how it achieved it. What

Re: [FRIAM] Deep learning training material

I was hoping this article would have more meat to it, but the main point seems highly relevant to a practical/introductory workshop such as the one you are developing: The Need for Interpretable Features: Taxonomy and Motivation

Re: [FRIAM] Sorting Algorithm? AI? Identifying "types" within data

>From what I can tell "one-hot encoding" is just another term for dummy coding the data, i.e., make it a bunch of 1/0 columns. H2o seems more promising, but seems to require a backbone of quantitative data that you can substitute (based on something akin to a regression) for the categorical

Re: [FRIAM] Deep learning training material

@Russ, a) I appreciate the suggestion to include a simple neural network that can make predictions based on inputs and be trained using steepest descent to optimize its weights. This would be a valuable addition to my training material, as it provides a foundational understanding of how neural