Gartner Research

How Augmented Machine Learning Is Democratizing Data Science

Published: 29 August 2019

ID: G00447964

Analyst(s): Jim Hare , Carlie Idoine , Peter Krensky

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.

Table Of Contents

Analysis

  • 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)

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