How to boost data science routines with DataArt’s AutoML Platform?
summary
Claims an AutoML platform that performs Automated Feature Engineering on relational (SQL) data, auto-detects types across up to five to seven joined tables, runs model selection and produces one-click deployment as a REST endpoint in a Docker/Flask container. Demonstrated a Kaggle-like run reaching top 3% with pure automation and a product-category model delivered to production in one week at 92% accuracy; typical POC time drops up to fourfold. Exposes an SDK in three lines, exports Python pipeline code, and uses LIME plus a "what‑if" tool for explainability.
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chapters (7)
- 0:00Introduction
- 2:54AutoML platform origin
- 5:45Accelerating data science
- 11:03Live demo
- 16:10Business impact and use cases
- 18:34Automating routines
- 21:43Q&A
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