CHAMPAIGN, Ill., June, 14, 2018 /PRNewswire/ -- Wolfram Research, makers of Mathematica, Wolfram|Alpha and the Wolfram Language, officially launches the Wolfram Neural Net Repository. Providing immediate access to neural networks for AI and machine learning applications, the repository further builds a ubiquitous layer of computational intelligence upon the Wolfram tech stack. These models are suitable for immediate evaluation, training, visualization, and transfer learning, for both experts and those new to applying AI to their work.
Building on the Wolfram Language Neural Net Framework introduced in 2014 with Version 10 of the Wolfram Language, the repository provides a uniform system for storing and deploying neural network models in an immediately computable form. The repository is built to be a global resource for neural net models, including those from the latest research papers, as well as ones trained or created at Wolfram Research.
"Machine learning is a field in hypergrowth right now—with interesting new results being published every week. Our goal with the Wolfram Neural Net Repository is to let people immediately integrate the latest research neural nets into their work," said Stephen Wolfram, founder and CEO of Wolfram Research. "Like everything we do with Wolfram Language, our goal is to make everything as smooth and automated as possible, so it's immediate to include a new neural net from the repository, with all encoding, decoding, etc. handled automatically."
Curated by researchers and scientists who have helped drive Wolfram Research's 30 years of continuous R&D, the neural net models are accessible in the Wolfram Cloud and can be exported in the popular MXNet framework. These nets are suitable for a variety of applications including classification, feature extraction, image processing, language modeling, speech recognition, and regression. The growing number of models work with text, image and numerical inputs for quick prototyping of neural net solutions for multiparadigm data science applications.
The ease of access and use of the repository on desktop, cloud, or on a mobile device, brings unparalleled flexibility to training and deploying AI solutions to a wide range of problems in business, research, data science, software development, and beyond, in labs, classrooms, or enterprise.
Further details on the Wolfram blog.
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SOURCE Wolfram Research