Recent content by alfiethinker42

A useful way to understand Deep Learning is to separate the goal, the input, the model or tool, and the way the output is evaluated. One important area is cost control. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell what...

The point about step and beginner is interesting. In practice I would keep the first test simple, record what worked, and only add extra complexity if it solves a specific limitation. It is usually easier to troubleshoot when each change is tested on its own.