ABBYY recently announced the launch of NeoML, an open-source library for building, training, and deploying machine learning models. NeoML is a cross-platform framework optimized for applications that run in cloud environments, on desktop and mobile devices. It supports both deep learning and traditional machine learning algorithms.
NeoML framework is used by ABBYY engineers for computer vision and natural language processing tasks, including image preprocessing, classification, document layout analysis, OCR, and data extraction from structured and unstructured documents.
In terms of performance, “NeoML offers 15-20% faster performance for pre-trained image processing models running on any device*.” NeoML has been 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.
Features:
- It comprises of neural networks with support for over 100 layer types
- It supports traditional machine learning: 20+ algorithms (classification, regression, clustering, etc.)
- It supports CPU and GPU along with the fast inference
- It supports ONNX (The Open Neural Network Exchange)
- It supports languages like C++, Java, Objective-C. Python will be added shortly
- It supports cross-platform. the same code can be run on Windows, Linux, macOS, iOS, and Android
Github: https://github.com/neoml-lib/neoml
Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.
