ChatGPT can be your companion Data Scientist, but only if you know how to ask it nicely… Here is a quick rundown of how ChatGPT helped me estimate missing heart rate training data from a few other training sessions, a simulated “supervised machine learning” solution.
On September 14, 2024, I was out riding my bike. I typically track my heart rate zones as zone 2 & 3 cardio are basically the fountain of life. During this ride, my heart rate sensor, a polar h10, stopped gathering data, so I ended up with a 90 min session with no data, yikes!
What to do, what to do… if you have been following the whole “AI Thing” by now I’d “assume” (ass of you and me) that you you understood that LLMs were really good at observing and generating patterns. In fact, an LLM is “nothing more” than a canned observation of patterns capable of making more patterns, kind of like a self quilting quilt that had instead of a yarn structure, a structure made of all publicly known information and instead of knots in the quilt, the LMM produces any text output given some inputs.
Ok so back to my conundrum, how do I get my data if my sensor stopped recording?
Well, I knew that I had other properly recorded sessions, so like a good data scientist, I knew that I had a few examples of “supervised training data”, ie, i knew there were some inputs, like, speed, distance, pace (and gps data) that produced some output → my heart rate. In this particular instance, because I used the polar flow app, my training session had no sensor HR data, but it did have the speed, distance and pace data…
Go Go Gadget Data Interpolation → “Supervised Learning” Without Running any Code !!!