Amazon and Microsoft on Thursday rolled out open-source software called Gluon in the stated hope of simplifying the implementation of machine learning.
Gluon provides an interface, in the form of an API, for building neural networks, something that's not all that easy to do for those not steeped in the art.
The software, available under the Apache 2.0 license, allows developers to construct machine learning models with the help of modular components.
Supporting both traditional imperative programming and symbolic programming – where computational results are represented in a graph – Gluon is essentially an abstraction layer designed to work with deep-learning frameworks Apache MXNet and, soon, Microsoft's Cognitive Toolkit.
"Developers who are new to machine learning will find this interface more familiar to traditional code, since machine learning models can be defined and manipulated just like any other data structure," said Matt Wood, general manager of AI and deep learning services at AWS, in a blog post today.
"More seasoned data scientists and researchers will value the ability to build prototypes quickly and utilize dynamic neural network graphs for entirely new model architectures, all without sacrificing training speed."