A Zero-Code Machine Learning Solution Based on MindsDB
With the built-in Lightwood frame, the following steps can be followed:
- Data preparation phase: Connects directly to the business database using the
SELECTstatement to extract historical sales data (need to include target forecast fields such assales_volume) - Model Creation: Execute a single SQL command
CREATE PREDICTOR sales_forecast FROM database.sales_data PREDICT sales_volume - automatic training: The system automatically handles feature engineering, algorithm selection and hyper-parameter optimization, and the training progress can be viewed in real time in the web interface.
- Predictive applications: Use
SELECT sales_forecast.sales_volume FROM sales_forecast WHERE quarter='Q3-2025'Access to forecast results
Advantage Statement: A retail customer completed the entire process from data connection to predictive application in 2 hours, saving 85% development time compared to traditional solutions. Supports regular usageRETRAINcommand to update the model.
This answer comes from the articleMindsDB: An Open Source Platform for Connecting Data from Multiple Sources and Querying with SQL and AIThe
May not be reproduced without permission:AI productivity tools " How to achieve rapid deployment of sales forecasting models without writing complex code?
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