Automated Data Science
Optimize your machine learning (ML) model development for high performance and accuracy
Request Demo
Data Science Automation
Automate the end-to-end process of feature engineering and selection by using in-built capabilities. Make use of AutoML to achieve the best possible model performance and improve it further with automated hyperparameter tuning. Leverage the one-click option to deploy the model once it’s developed and evaluated

Automated Feature Engineering
- Create various features automatically from different datasets by analyzing the relationship between columns and tables
- Generate new features with the automated handling of the depth of the relationship between datasets
- Add custom rules while creating new features
Automated Feature Selection
- Achieve better model performance using ML-based feature selection from thousands of features to choose from
- Get automated feature validation options based on the type of modeling algorithm

High-performance Auto ML
- Get the best-suited model performance, with ML auto-selecting ideal pre-processing modeling algorithms and parameter configuration
- Improve model performance with automated hyper parameter tuning through several optimization techniques, such as grid search, Bayesian optimization, etc.
- Optimize the computation costs by using time-bound auto ML capabilities
Automated Model Deployment and Retraining
- Ensure one-click deployment once the model is developed and evaluated
- Leverage auto model retraining and selection based on a predefined frequency or an event
Capabilities of Newgen AI Cloud