Repost: AutoML Tools Emerge as Data Science Difference Makers

Media Coverage: AutoML Tools Emerge as Data Science Difference Makers

August 29, 2019

Ryohei Fujimaki, CEO of dotData, recently sat down with @datanami’s Alex Woodie to discuss how #AutoML tools are beginning to emerge and make a real difference in the #datascience world.   #machinelearning #AI

Machine learning tools are being used in data science to imbue intelligence into products and services. In the past few years, automated ML tools have gained popularity, including AutoML tools. Forrester says companies will have a stand-alone AutoML tool. Gartner says data scientists will be using tools to automate their tasks. Forrester analysts gave high marks to DataRobot, H2O.ai, and dotData, the three leading AutoML solutions providers. H2O.ai and DataRobot have the most customer deployments, DataRobot has the biggest funding, and dotData has solid capabilities but is still building market recognition.

Fujimaki says dotData has a GUI that leads users through building machine learning models, and more advanced users use a Python interface to control the modeling process. AutoML vendors Aible, Bell Integrator, Big Squid, DMway Analytics, EdgeVerve, and Squark made Forrester’s cut for the new AutoML Wave. Databricks hopes to help data scientists, data engineers, and citizen data scientists build machine learning applications. With the growth of cloud solutions, AutoML solutions on the cloud are also expected to see plenty of use. Read the full article at Datanami.

dotData

dotData Inc.

dotData Automated Feature Engineering powers our full-cycle data science automation platform to help enterprise organizations accelerate ML and AI projects and deliver more business value by automating the hardest part of the data science and AI process – feature engineering and operationalization. Learn more at dotdata.com, and join us on Twitter and LinkedIn.