NEXT is a machine learning system that runs in the cloud and makes it easy to develop, evaluate, and apply active learning in the real-world. Ask better questions. Get better results. Faster. Automated.
A data processing pipeline that schedules and runs content harvesters, normalizes their data, and outputs that normalized data to a variety of output streams. This is part of the SHARE project, and will be used to create a free and open dataset of research (meta)data. Data collected can be explored at https://osf.io/share/, and viewed at https://osf.io/api/v1/share/search/. Developer docs can be viewed at https://osf.io/wur56/wiki
A Swift library that uses the Accelerate framework to provide high-performance functions for matrix math, digital signal processing, and image manipulation.
Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.
This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is
solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.