With MLOps you can deploy Python code straight into production without rewriting it, saving you time & resources without sacrificing accuracy or performance.
Iguazio listed as Sample Vendor in Five 2021 Gartner Hype Cycles
With the explosion of the machine learning tooling space, the barrier to entry has never been lower for companies looking to invest in AI initiatives. But enterprise AI in production is still immature. How are companies getting to production and scaling up with machine learning in 2021?
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.