Node-RED and TensorFlow.js: Developing deep learning IoT apps in the browser
Who is this presentation for?
- Developers and educators
Node-RED is an open source visual programming tool built on Node.js, capable of wiring together hardware devices, APIs, and online services in new and interesting ways. Node-RED users range from beginning developers to experts running complex workflows. Thanks to TensorFlow.js and the ability to run models in the browser, these assets can now be introduced into the Node-RED environment and interacted with in a visual, user-friendly way.
What you'll learn
- Learn how to develop applications with Tensorflow.js models in Node-RED
- Identify a new tool for exposing early developers to machine learning models
va barbosa is a developer advocate at the Center for Open-Source Data & AI Technologies at IBM, where he helps developers discover and use data and machine learning technologies. This is fueled by his passion to help others and guided by his enthusiasm for open source technology. Always looking to embrace new challenges and fulfill his appetite for learning, he immerses himself in a wide range of technologies and activities. When not focusing on the developer experience, he enjoys dabbling in photography. If you can’t find him in front of a computer, try looking behind a camera.
Paul Van Eck
Paul Van Eck is a software engineer in the Cognitive OpenTech Group at IBM. Over the past few years, he’s been actively involved in open source AI technologies such as PyTorch and TensorFlow. With several years of web development experience, Paul has an express interest in browser-based machine learning. He’s worked on projects leveraging TensorFlow.js and still aims to explore other possibilities in this intersection of technologies.
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