There are several ways to approach Deep Learning, so I wanted to compare experiences.
I am particularly interested in future improvements and troubleshooting. I would like to compare approaches that people have actually used rather than just theoretical suggestions.
What trade-offs have you found between quality, speed, cost, and reliability?
I am particularly interested in future improvements and troubleshooting. I would like to compare approaches that people have actually used rather than just theoretical suggestions.
What trade-offs have you found between quality, speed, cost, and reliability?