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If your schedule is so irregular/erratic, how is a ML algorithm supposed to be able to learn it? Sounds like in that case it's better to just control things ma
by capableweb 4y ago
If your schedule is so irregular/erratic, how is a ML algorithm supposed to be able to learn it?
Sounds like in that case it's better to just control things manually.
- bryanrasmussen 4y agoML can learn patterns that humans might not be aware of, so you there might be certain things that happen that show you will be on a mission to East Asia for a couple days.
- deleted 4y ago[deleted]
- tomrod 4y agoOnly when data is supplied to it to match the trained pattern, ML is pattern recognition. Anything outside of that is still AI, but it isn't ML. I can think of very few feature sets we could supply to help predict someone will be deployed to East Asia for a few days other than scraping calendars and mail for religious and military organizations. From a design perspective, Nest and others are either additively learning in situ to enhance a base model or they are working from a base model that doesn't directly learn, just classifies workflow to categorize observations on a base model. I doubt heavy training is occurring where the Nest and similar is treated as the central compute node.