FlexSearch.js: A Full Text Search Library — Claims to outperform all of the alternatives while supporting features like multi-word matching and phonetic transformations. Happy in both the browser and Node.js.
💬 A Q&A with… Sandeep Gupta Product Manager for TensorFlow.js at Google Mountain View, CA
TensorFlow is a predominantly Python-oriented open source machine learning framework (and dataflow programming in general) originally developed at Google that has seen a burst in popularity recently.
How do you see TensorFlow.js opening up new opportunities versus the more established Python and C TensorFlow worlds?
In the browser, TensorFlow.js offers unique opportunities by taking advantage of the interactive user experience, sensors such as webcam, microphones, GPS, etc, and the ability to offer rich, real-time visualization experiences. See some fun demos here. For enterprises using Node.js, building ML solutions using TensorFlow.js means that the same teams working on their backend infrastructure can also integrate ML pipelines directly without having to stand-up separate Python-based data-science teams.
What’s the most interesting use of TensorFlow.js you’ve seen so far?
We are continuously surprised by novel and interesting use cases of TensorFlow.js. Several examples are listed here in our gallery page. We love projects like Creatability and Handsfree.js, which allow you to make more accessible and handsfree interfaces and experiences for the Web and open incredible new opportunities. With server-side TensorFlow.js, Magenta Studio has built several amazing music generation plug-ins using powerful ML techniques.
While machine learning is perhaps the most noteworthy use case for TensorFlow, what interesting uses for TensorFlow.js do you see outside of that space?