The WebGL-accelerated library works with the Node.js server-side JavaScript runtime, but isn’t on par with Tensorflow’s Python API Credit: Thinkstock Google’s TensorFlow open source machine learning library has been extended to JavaScript with Tensorflow.js, a JavaScript library for deploying machine learning models in the browser. A WebGL-accelerated library, Tensorflow.js also works with the Node.js server-side JavaScript runtime and is part of the TensorFlow ecosystem. With machine learning directly in the browser, there is no need for drivers; developers can just run code. The project, which features an ecosystem of JavaScript tools, evolved from the Deeplearn.js library for browser-based machine learning; Deeplearn.js is now known as Tensorflow.js Core. TensorFlow.js APIs can be used to build models using the low-level JavaScript linear algebra library or the higher-level layers API. TensorFlow.js model converters can run existing models in the browser or under Node.js. Existing models can be retrained using sensor data connected to the browser. A tensor serves as the central unit of data. Also, a high-level, Keras-inspired API is included for building neural networks. But TensorFlow.js is not the only JavaScript library built for neural networking; TensorFire, built by MIT students, executes neural networks in a webpage. Tensorflow.js has an API similar to Tensorflow’s Python API. But the JavaScript API does yet not support all the functionality of the Python API. Builders of Tensorflow.js pledge to achieve parity where it makes sense but want to provide an idiomatic JavaScript API. TensorFlow with WebGL also runs at 50 to 60 percent the speed of the TensorFlow Python API usedwith the AVX library. Planned enhancements for TensorFlow.js include: A visualization library to perform quick visualizations of the model and data. Performance improvements in the browser. WebGL optimization. A browser- and Node-specific data API. Cloud integration on the Node.js side, including serverless-type integration points. Better async support with the libuv asynchronous I/O library. Where to download TensorFlow.js You can download TensorFlow.js from GitHub. Related content analysis Beyond the usual suspects: 5 fresh data science tools to try today The mid-month report includes quick tips for easier Python installation, a new VS Code-like IDE just for Python and R users, and five newer data science tools you won't want to miss. By Serdar Yegulalp Jul 12, 2024 2 mins Python Programming Languages Software Development analysis Generative AI won’t fix cloud migration You’ve probably heard how generative AI will solve all cloud migration problems. It’s not that simple. Generative AI could actually make it harder and more costly. By David Linthicum Jul 12, 2024 5 mins Generative AI Artificial Intelligence Cloud Computing news HR professionals trust AI recommendations HireVue survey finds 73% of HR professionals trust AI to make candidate recommendations, while 75% of workers are opposed to AI making hiring decisions. By Paul Krill Jul 11, 2024 3 mins Technology Industry Careers how-to Safety off: Programming in Rust with `unsafe` What does it mean to write unsafe code in Rust, and what can you do (and not do) with the 'unsafe' keyword? The facts may surprise you. By Serdar Yegulalp Jul 11, 2024 8 mins Rust Programming Languages Software Development Resources Videos