Google is offering an open source, hardware-accelerated library for machine learning that runs in a browser.
The library is currently supported only in the desktop version of Google Chrome, but the project is working to support more devices. The Deeplearn.js library enables training of neural networks within a browser, requiring no software installation or back end. “A client-side ML library can be a platform for interactive explanations, for rapid prototyping and visualization, and even for offline computation,” Google researchers said. “And if nothing else, the browser is one of the worldrsquo;s most popular programming platforms.”[ Learn how to write apps that take full advantage of machine learning: Data in, intelligence out: Machine learning pipelines demystified • Googlersquo;s machine-learning cloud pipeline explained • R and Python drive SQL Server 2017 into machine learning. | Keep up with hot topics in programming with InfoWorldrsquo;s App Dev Report newsletter. ]Using the WebGL JavaScript API for 2D and 3D graphics, Deeplearn.jsnbsp; can conduct computations on the GPU.
This offers significant performance, thus getting past the speed limits of JavaScript, the researchers said.To read this article in full or to leave a comment, please click here
The library is currently supported only in the desktop version of Google Chrome, but the project is working to support more devices. The Deeplearn.js library enables training of neural networks within a browser, requiring no software installation or back end. “A client-side ML library can be a platform for interactive explanations, for rapid prototyping and visualization, and even for offline computation,” Google researchers said. “And if nothing else, the browser is one of the worldrsquo;s most popular programming platforms.”[ Learn how to write apps that take full advantage of machine learning: Data in, intelligence out: Machine learning pipelines demystified • Googlersquo;s machine-learning cloud pipeline explained • R and Python drive SQL Server 2017 into machine learning. | Keep up with hot topics in programming with InfoWorldrsquo;s App Dev Report newsletter. ]Using the WebGL JavaScript API for 2D and 3D graphics, Deeplearn.jsnbsp; can conduct computations on the GPU.
This offers significant performance, thus getting past the speed limits of JavaScript, the researchers said.To read this article in full or to leave a comment, please click here
