There are several ways to approach Machine Learning, so I wanted to compare experiences.
I am particularly interested in common mistakes and reliability. 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?
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I am particularly interested in common mistakes and reliability. 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?
Photo by on
