by Angela Guess

According to a recent press release, “Feedzai has launched the Feedzai OpenML Engine, in response to recognizing the need for data science teams to utilize their own tools and expertise. Built on Feedzai’s distributed microservices architecture, this powerful service allows data scientists to bring their preferred machine learning modeling and runtime frameworks, including open source, research, or commercial, to the Feedzai platform. Initial product support includes an SDK for Python, R, and Java, and it provides close integration with any open source library, sourcing framework, and modeling environment.”

The release goes on, “The three main innovations in Feedzai’s OpenML framework include: (1) Use any language or environment for data science activities: Feedzai is removing the burden of data scientists to work in a singular environment dictated by a third-party vendor. Feedzai is also removing the bottleneck where clients require vendors to create models on their behalf… (2) Leverage emerging algorithms as they become available: The OpenML Engine allows data science teams to leverage pre-written machine learning libraries from any open source (e.g., TensorFlow, H20.ai, Spark’s MLib, scikit-learn). By opening up Feedzai’s real-time engine to use an open score approach, any external library or scoring framework can be used in conjunction with Feedzai. (3) Enables automated end to end connectivity across the data science ecosystem: The OpenML Engine enables the automation of model creation and deployment, whether these models are built inside or outside Feedzai’s platform. This end-to-end connectivity and automation provides seamless integration with Feedzai’s real-time processing for decision-making.”

Read more at Business Wire.

Photo credit: Feedzai