To ensure a smooth first-time experience, users are advised to pay special attention to the following three points:
- Data preparation specifications
- Ensure CSV file encoding is UTF-8
- It is recommended that the date and time columns be in a uniform format such as YYYY-MM-DD.
- Remove complex formatting such as merged cells
- Target variable selection
- Classification problems need to ensure a balanced sample of categories (at least 50 records per category)
- The regression problem requires checking that there are no anomalous outliers in the target value
- Validation of results
- Pay attention to platform alerts warning of data quality issues
- For business-critical decisions, it is recommended to review the model effects by dividing the validation set.
The platform provides sample datasets and step-by-step wizards, and first-time users are recommended to familiarize themselves with the process by using demonstration projects such as "Titanic Survival Prediction".
This answer comes from the articleDataFawn: A Data Analytics Platform for Building Machine Learning Models Without Writing CodeThe
May not be reproduced without permission:AI productivity tools " What are the key points to keep in mind when a novice uses DataFawn for their first data analysis?
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