I wanted to start a broader mistakes and lessons thread around Datasets.
A useful angle is advanced workflows, but it also connects with learning curve. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where Datasets is genuinely useful and where it still needs improvement.
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A useful angle is advanced workflows, but it also connects with learning curve. Different tools and workflows can produce very different results even when the goal is similar.
It would be interesting to compare practical examples, experiments, setups, or lessons that show where Datasets is genuinely useful and where it still needs improvement.
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