Getting started with Bayanii
A quick guide to going from a CSV file to a working model.
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1
Prepare your data
Export your data as a CSV with a header row. Each column is a feature; one column is the value you want to predict (your "target"). More clean rows generally means a better model.
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2
Create an account and upload
Sign up, then upload your CSV. Bayanii reads the columns and shows a preview plus basic data-quality checks.
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3
Pick a task and target
Choose regression (predict a number), classification (predict a category), or forecasting (predict future values over time), then select your target column.
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4
Train and review
Bayanii trains a lineup of models and picks the best. Review the accuracy, charts and the model card to decide whether the result is good enough.
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5
Use and export
Upload new data or fill a form to get predictions, then export the results as a CSV for your reports and workflows.
Tips for a better model
- Remove ID-like columns (row numbers, unique codes) — they don't help prediction.
- For forecasting, include a clean date/time column with regular intervals (daily, monthly, …).
- Aim for at least a few hundred rows where you can.
- Check the data-quality findings — Bayanii flags issues it can't fix for you.