Augmented machine learning, which helps both expert and citizen data scientists build and deploy models more quickly, has become one of the most transformational innovations in data science and machine learning (DSML).
We believe, Gartner’s report, How Augmented Machine Learning Is Democratizing Data Science, can help data and analytics leaders understand how to increase data science productivity, reduce skills shortages, and facilitate collaboration through the introduction of augmented DSML capabilities.
According to Gartner, there are four major types of DSML delivery approaches – packaged depending on skills, speed to use and deploy, variety of supported algorithms, and flexibility and breadth of use cases. Read this important report to discover the approach that’s the best fit for you.
Read this report now to learn how augmented DSML:
- Enables organizations to bring sophisticated data science to bear on key problems without needing the same critical mass of expert data science talent.
- Relieves the tedious portions of experts' workloads and helps citizen data scientists break through barriers to entry in ML.
- Improves the ROI of data science investments, reduces time to value and expands the footprint of ML.