[getpokedagain]

I worked (professionally) on a product a few years ago based upon decision tree and random forest classifiers. I had no background in the math and had to learn this stuff which has payed dividends as llms and AI have become hyped. This is one of the best explanations I've seen and has me super nostalgic for that project.

Gonna try to cook up something personal. It's amazing how people are now using regression models basically all the time and yet no-one uses these things on their own.

[jjcc]

I worked on a product which was the best ID reader in the world at the time 25 years ago. The OCR engine was based on Decision tree and "Random Forest" (I suspect the name did exist) with only 3 trees. It was very effective as a secret weapon of the competitiveness. I tried to train a NN with a framework called SNNS(Stuttgart Neural Network Simulator) as the 4th tree complement to the existing 3.

Today, hand writing OCR is a "hello world" sample in Tensorflow.

[getpokedagain]

That's awesome and based on my experience I'm not shocked this went well. I'm not sure what the features would be in this but I am assuming they could be specific pixel combinations or other things which would be easily labeled in a few ways. I hope you had fun with it.

My previous project was far from that. https://healthverity.com/audience-manager/

I had a lot of fun, really the last fun project I've had. I hope you had fun as well.

[mistrial9]

in the interest of understanding, is there any code or similar for the approach? does that OCR run anywhere today?