Recent content by kaiwolf72

There are several ways to approach Deep Learning, so I wanted to compare experiences. I am particularly interested in setup choices and common mistakes. I would like to compare approaches that people have actually used rather than just theoretical suggestions. What has worked best for you, and...

I think startups and cost is the key part of this topic. A practical approach is to define the outcome you want, test it with a small example, and then check quality, speed and reliability separately. It also gives you a cleaner baseline if you want to compare tools or settings later.

This tutorial shows a simple repeatable way to work with Machine Learning while focusing on customisation. Step 1: Define the result you want. Write down the output format, quality requirements, and any limits before you start. Step 2: Prepare a small representative example. Test with...