Media Coverage: AutoML Tools Emerge as Data Science Difference Makers
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.