The same pipeline runs behind almost every AI system. Data comes in, gets cleaned and split, the model trains by finding the statistical patterns that link inputs to answers, and then it is graded on examples it has never seen. If it fails, the loop starts again with better data. Tap any stage to see what it does, or press Run the pipeline.
01
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Collect
Raw labeled examples arrive
✓
02
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Clean
Fix errors, drop junk
✓
03
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Prepare
Split: train vs. hidden test
✓
04
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Train
Learn the patterns in the data
✓
05
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Evaluate
Grade it on unseen examples
✓
06
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Model ready
Predict on new inputs
✓
not good enough? → back for more & better data
ReadyPress Run the pipeline to watch a dataset travel from raw rows to a trained model — or tap any coloured stage above to see what it does.