The average for 1st day churn hovers at 70%. The solution? Predict user retention in the crucial first seconds and minutes after a new user onboards.
On-demand webinar with Microsoft & Github: Git-Based CI / CD for Machine Learning & MLOps
We are delighted to announce that Iguazio has been named a sample vendor in the 2020 Gartner Hype Cycle for Data Science and Machine Learning, as well as three additional Gartner Hype Cycles for Infrastructure Strategies, Compute Infrastructure and Hybrid Infrastructure Services, among industry leaders such as DataRobot, Amazon Web Services, Google Cloud Platform, IBM and Microsoft Azure.
Effectively bringing machine learning to production is one of the biggest challenges that data science teams today struggle with. MLOps is the solution.
Version 2.8 includes an exciting set of features that help users to build and manage their operational machine learning pipelines. We’ve introduced a new set of functionalities around MLOps which assists in solving some common challenges in bringing AI to production. And this is only the beginning.
Data science has come a long way, and it has changed organizations across industries profoundly. Very reliable systems and automated algorithms are being developed to harness this data to deliver increased efficiency and value to humanity.
Data science needs to quickly adapt to the fast-paced changes happening all over the world. Currently, many businesses are in a tough spot, and having the right kinds of data and intelligence enables them to react quickly to the unprecedented changes brought about by the pandemic.