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Home Machine Learning

ABBYY Open-Sources NeoML Machine Learning Library

June 17, 2020
in Machine Learning
ABBYY Open-Sources NeoML Machine Learning Library
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ABBYY has announced the launch of NeoML, an open-source library for building, training, and deploying machine learning models. NeoML supports both deep learning and traditional machine learning algorithms and is optimized for applications deployed in cloud environments, on desktop systems, or mobile devices.

Faster image processing

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The digital intelligence firm claims NeoML offers between 15 and 20 percent faster performance for pre-trained image processing models running on any device when compared to a popular open-source library that the firm benchmarked.

NeoML is designed as a universal tool to process and analyze data in a variety of formats including text, image, video, and others. It supports ​​C++, Java, and Objective-C programming languages. Python will be added shortly.

The library is fully cross-platform, with a single code base that can be run on all popular operating systems including Windows, Linux, macOS, iOS, and Android. It is also optimized for both CPU and GPU processors.

The combination of higher inference speed with platform-independence makes the library ideal for mobile solutions that require both seamless customer experience and on-device data processing, says ABBYY.

Developers can use NeoML to build, train, and deploy models for object identification, classification, verification, and predictive modeling to achieve various business goals. Banks can develop models to manage credit risk and predict customer churn, and retail and fast-moving consumer goods (FMCG) companies can analyze the performance of marketing campaigns.

“The launch of NeoML reflects our commitment to contribute to industry-wide AI innovation,” said Ivan Yamshchikov, AI Evangelist at ABBYY, who noted that ABBYY has a proven track record of innovation with over 400 patents and patent applications globally.

“Sharing our framework allows developers to leverage its inference speed, cross-platform capabilities, and especially its potential on mobile devices, while their feedback and contribution will grow and improve the library. We are thrilled to promote advancements in AI and support machine learning being applied to increasingly high-value and impactful use cases.”

NeoML is licensed under the Apache License 2.0 and is currently available on GitHub here.

Photo credit: iStockphoto/MchlSkhrv

 

Credit: Google News

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