My Meeting Experience

For my Python Meetup experience, I digitally engaged in the Austin Monthly Python meetup on November 9th where Nick Schenone and Dima Kniazev were invited to talk about building an AI App using MLRun and using Redis, respectively. The immediate thing that comes to mind when I look back on this experience is a foundational idea that I’ve talked a lot in reference to digital humanities in other classes: the idea of interdisciplinary work through the use of digital tools. During class we’ve done mostly completed field-independent work that’s dealt soley with how we can directly engage tools in order to accomplish tasks that don’t necessarily have a large bearing on other fields outside computer sciences and engineering. But with the speakers that were invited, I got a chance to see how raw programming directly connected to the fields of economics and healthcare through our speakers. Going into the session, I sort of expected the speakers to be very techno-babbly–which they were to a degree–but they were also very aware of the “why” of the code that they demonstrated to us. With these thoughts on the table, I definitely see the value in going to events like this when coding is talked about in regard to how it works with other studies, projects, and beyond.

There definitely was a disconnect in the meeting on my side that came from a still-growing foundation regarding vocabulary, tools, and the broader community. While listening to Nick talk about MLRun and MLOps, he talked about programming governance, orchestration, model registration, and other things that all required a quick Google search in order to make sure I was at least keeping up with the basic flow of the conversation. When Nick talked about a lot of the code and features, he tended to make comments that implied it was expected that people listening in already understood what he was trying to explain in regard to features of Machine Learning. It was a tad frustrating, but I can understand why, since these talks are geared towards active users in the programming community. With Dima, I actually enjoyed his talk of Local and Remote Model Deployment Strategies, as it gave me a deeper insight of how personal and cloud computing works. The final disconnect came in the programs that they talked about. While we got a short look at GitHub at one point, we heard about HuggingFace, Gradio, and Steamlit, all different applications intended to help built and implement programs. While I’m not sure where my programming practice and learning will take me in the future after this class, it’s nice to have received a tiny bit of insight into some programs outside Trinket so that I can fiddle with them in the future to see how I can approach programming in different ways.

While I had my difficulties following some aspects of the meeting, I can definitely see the significance in going and participating in these sorts of events. I think that, if I continue my programming learning outside this class in the future, I could see myself participating in events like this in the future. Having the chance to see how professional programmers work within different fields provides a new line of thinking that I otherwise would not have known about otherwise.

Meeting Links

The links for these meetings are available on Youtube via the Austin Python Meetup channel, so I’m linking them here for anyone else who would like to view them if they read this:

Dima Kniazev’s Using Redis as Online Feature Store for Real-time Inference

Nick Schenone’s Building an AI App in Under 20 Minutes Using OS MLOps tool MLRun

Thanks for the read!