Week 20 Lindahl Letter recap edition
Writing a Substack for the last 20 weeks has been an interesting endeavor to undertake. Frequently to conduct research I go out and engage in exploratory efforts to really understand new technology and what is involved in being a part of it in practice. Part of that was learning how to set up a Substack, trying to get subscribers, and sticking to a publishing schedule. Having the agenda setup for the first 30 weeks or so was key to kick starting this effort. For me the personal investment into the activity helps me demonstrate mastery of it and it helps me figure out how to add value from that activity. Part of this enterprise for the last 20 weeks has been to distill the chaotic and ever changing landscape of artificial intelligence and machine learning into distinct trends and single serving topic reviews that are highly consumable. Getting to that point of communication and writing on a weekly basis is what this effort has been about. You are welcome to be the judge of the success or failure of that effort.
Right now arriving in your inbox happens to be the 20th edition of the Lindahl Letter. Links to the first 19 weeks are listed below. Feel free to check them out if you missed some of them or if you just want to review what was covered from the start until now. Probably the most essential part of everything that I have communicated can be summed up simply as the assertion, “make sure you have an ML strategy and work to execute that by monitoring your ROI on the activities you elect to undertake.”
The week by week Lindahl Letter roundup
Week 1: Machine Learning Return On Investment (MLROI)
Week 3: Machine learning Teams
Week 4: Have an ML strategy… revisited
Week 5: Let your ROI drive a fact-based decision-making process
Week 6: Understand the ongoing cost and success criteria as part of your ML strategy
Week 11: What is ML scale? The where and the when of ML usage
Week 13: Building out your ML Ops
Week 15: What are people really doing with machine learning?
Week 16: Ongoing ML cloud costs
Week 17: Figuring out ML readiness
Week 18: Could ML predict the lottery?
Week 19: Fear of missing out on ML
Links and thoughts:
Go check out episode #54 of Machine Learning Street Talk with Gary Marcus and Luis Lamb covering the topic of “Neurosymbolic models”
Check out this album from Google Cloud Tech “What is Kf?” I liked the graphics explaining the workflows
This is a fun little video from Microsoft Developer titled “Learn Azure Your Way Pt. 2”
I watched maybe 30 minutes of the WAN show this week with Linus and Luke
Top 6 Tweets of the week:
Footnotes:
None this week.
What’s next for The Lindahl Letter?
Week 21: Doing machine learning work
Week 22: Machine learning graphics
Week 23: Fairness and machine learning
Week 24: Evaluating machine learning
Week 25: Teaching kids ML
I’ll try to keep the what’s next list forward looking with at least five weeks of posts in planning or review. If you enjoyed reading this content, then please take a moment and share it with a friend.