Published: 29 August 2019
Summary
Augmented analytics has emerged as one of the most transformational innovations in data science and machine learning. It helps expert and citizen data scientists more quickly build and deploy models. Data and analytics leaders need to understand the benefits and limitations of augmented DSML.
Included in Full Research
- Data Management
- Model Selection
- Model Training and Tuning
- Model Deployment and Operationalization
- Augmented DSML Packaging and Delivery
- Build Your Own Platforms (Mix and Match)
- Commercial DSML Platforms (Assisted Modeling)
- Citizen DSML Platforms (Automated Modeling)
- Cloud Services (APIs)