This week my time is going to be spent on working out my new speaking presentation. It is about time to get going on that project. At the moment, the working title of that talk is, “Effective ML ROI use cases at scale.” I’m not totally sold on that title and that might be why it is taking me so long to finish this presentation. Previously back in November I gave a talk in New York City about, “Figuring out applied machine learning: Building frameworks and teams to operationalize machine learning at scale. Thinking back on that now it was a very long title for a talk and a very different time before quarantine and the pandemic. Building that presentation ended up in a roughly 5,000 word presentation that was recorded into Mp3 format for easy listening. You can find that content here:
Writing this new paper is going to include a few different exercises along the journey. To help include you in the adventure I’m going to try to describe the process before it starts. Generally, I have used two different writing strategies to build out new presentations. One of these might work for you or might need an entirely different writing strategy. First, sometimes I just sit down and write the presentation from start to finish. Previously that has happened a few times and in one solid writing session driven by the headwinds of inspiration a paper goes from start to finish in one session. You could say in that example of a writing strategy you have to wait for the spark to strike and the paper will just end up happening. Second, I will take out one of my notebooks with blank pages and sketch out the structure of the paper and then start filling out the necessary sections like building random bricks in a wall. That analogy does not work in practice, but in the world of writing you can generally work on any part of the paper. That is the power of imagination within the process. Using a little bit of imagination you don’t have to build the paper from the bottom up like setting bricks in a wall.
Seriously, I’m not even entirely sold on the current writing project. It is a work progress to be sure. Three different titles have received attention; “Effective ML ROI use cases at scale”, “Building effective ROI ML use cases”, and “ML use cases at scale with effective ROI.” At some point along the way the title could even change. Right now the structure of the presentation is probably going to center on 5 solid ML use cases and how the ROI is calculated for those examples. That is probably all it will take to round out the presentation. My best to get this done is to start a shell in Microsoft PowerPoint tonight and work to get the PowerPoint slides built out one at a time. Completing the presentation in PowerPoint will allow me to have all my thoughts lined up and ready to present. The next step in the process would be to write out the complete talk. Working on that plan will generate another roughly 5,000 word block or prose that could be easily converted into some type of academic paper. It is possible that the paper will only surround the best use case or perhaps the machine learning return on investment model itself.