A zero-install browser tool provides a complete local pipeline for training and deploying TinyML vision models on ESP32 hardware in under 10 minutes.
TensorFlow.js: Machine Learning for the Web and Beyond
2 Pith papers cite this work. Polarity classification is still indexing.
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abstract
TensorFlow.js is a library for building and executing machine learning algorithms in JavaScript. TensorFlow.js models run in a web browser and in the Node.js environment. The library is part of the TensorFlow ecosystem, providing a set of APIs that are compatible with those in Python, allowing models to be ported between the Python and JavaScript ecosystems. TensorFlow.js has empowered a new set of developers from the extensive JavaScript community to build and deploy machine learning models and enabled new classes of on-device computation. This paper describes the design, API, and implementation of TensorFlow.js, and highlights some of the impactful use cases.
verdicts
UNVERDICTED 2representative citing papers
An optimized browser-based version of the prior Coconet model enabled the Bach Doodle to process over 55 million harmonization requests in three days while releasing the collected user data.
citing papers explorer
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WebSerial Vision Training for Microcontrollers: A Browser-Based Companion to On-Device CNN Training
A zero-install browser tool provides a complete local pipeline for training and deploying TinyML vision models on ESP32 hardware in under 10 minutes.
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The Bach Doodle: Approachable music composition with machine learning at scale
An optimized browser-based version of the prior Coconet model enabled the Bach Doodle to process over 55 million harmonization requests in three days while releasing the collected user data.