Moving along the tasking backlog

Writing has to be a part of my daily routine. Sometimes the plan breaks down and that does not happen. Overcoming that obstacle is an important part of making sure that writing is a continuous part of your daily routine. Writers write. That is what they do and how they do it. One of the more consistent themes in this weblog is writing about writing. Just the process of typing and writing for a bit is the very thing that breaks down blocking factors and helps the words flow like the second cup of coffee for the day. That first cup never really flows the same way. Maybe it will never get the same amount of fanfare, because it is simply not going to be met with the same amount of enthusiasm. That is essentially what happens when you start writing about writing. You end up going until something worthy of enthusiasm shows up.

Working on some deliverables

Routines have fallen way to a nearly endless stream of things that need to be delivered throughout the last few days. That happens from time to time. Tasks pile up and end up crushing routines. At the end of the day, I spent the last few minutes of the day working on a few things that needed to be done. One of them included putting together a little bit of content for a conference this summer.

DATAx 2020 Conference Topic Area: Machine Learning

Session Description (100 words inclusive of title):

Title: Figuring out applied ML: Building ROI models, repeatable frameworks, and teams to operationalize ML at scale.

Description: Solving the hard problems requires operationalizing ML at scale. Doing that in a definable and repeatable way takes planning and practice. Understanding how to match the deep understanding of subject matter experts to the technical application of ML programs remains a real barrier to applied ML in the workplace. Understanding applied machine learning models with strong potential return on investment strategies helps make delivery a definable and repeatable process.

Well that worked out to a total of 87 words. Maybe I should sit down and write another sentence to flush out the full 100 word quota.

3-Audience Takeaways

  1. Beginning to think about the process of building machine learning ROI models
  2. Setting the foundation for defining repeatable machine learning frameworks
  3. Building teams to operationalize machine learning at scale

Well that is the content I needed to generate before the end of the day. Tomorrow, I need to spend some time working on some new slides. That is going to take a little bit of focus. Some of that content was sketched out the other day by hand. Maybe I should have started with the end product in mind instead of some back of the napkin sketches on this one. That might have helped turn the slides into reality a little bit faster. This approach is really both delaying the final product and maybe improving it. Sometimes you have to produce a couple of drafts of something to get to the finish line. Other times you only need to sit down and write it one time to create the final product.

Reconciling a year

Well it appears that 2020 is here and moving along already. It takes time to realize that life remains more important than time, but time remains precious. Right now I want to sit down and spend the next thirty minutes producing prose for the sake of producing prose. That is where my time is going to be focused. Some of that has to be about focusing. Some of it has to do with using my time in the best possible way. This weblog post today will not have any featured image attached to it. I know it is better to have media attached to each post. Taking a photograph of something everyday should be relatively easy to accomplish. Using the keyboard on the Google Pixelbook Go has been pretty easy and it has been comfortable to use. Working to write a million words on this keyboard is a nobel goal that should be possible given enough time.

Yes, coffee happened

Coffee happened. This weekend seems to be devoid of any blocks of extreme writing time. Part of that a consequence of the drive between Colorado and Kansas. Last night I did intend to sit down and write for a little bit, but things ended up taking up my time. That is the one thing that is really hard to control. Really digging in and working on complex things takes time. I’m not in full control of my time anymore. That seems to happen as you get older and have more commitments. Life happens. Just like coffee happens. None of that stops me from engaging in better planning to find blocks of time to invest in the things that require my time to push them forward. One of those things has been really digging into advancing my current talk on machine learning and trying to take some of the later sections to the next level.

Early next year, I will circle back and record audio for each of these weblog posts. I have not figured out a really solid method to record audio on my Google Pixel 4 XL smartphone and post that audio to this weblog. The new Google Recorder app produces audio files in a m4a format that this weblog platform does not ingest and display. I had messed around with trying to figure out how to convert m4a to mp3 via some type of application on my smartphone. It is relatively easy to make the conversion from the Audacity audio software, but that requires using a Chromebook/desktop computer.

The next version of my presentation is going to go deeper into examples and be more practical. A few new slides are under development:

  1. Example ML strategy
  2. Vector aligned ML ROI examples
  3. Example compendium of ML KPIs

Looking at guitars

This is a recording of my blog from December 19, 2019

This morning I spent some time looking at guitars online. Advertisements are everywhere this time of year and some of them are for guitars that look pretty awesome. The one that caught my eye this morning was a, “Chapman Ghost Fret Pro Limited Edition Electric Guitar Bad Blood.” It sports a guitar top that looks pretty epic based on some sandblasting and special color efforts.