TensorFlow.js
TensorFlow.js is a JavaScript library for developing and running machine-learning models in browsers, Node.js, and other JavaScript environments.
Deep Learning with Python, Third Edition
A JavaScript TensorFlow ecosystem library for running models in browsers or other JavaScript environments.
- How it is used
- Deploys trained models for local inference in browser and Electron JavaScript applications.
- How deep it goes
- Explains model import, device constraints, privacy, and optimization choices without detailing TensorFlow.js implementation internals.
- Examples
- Uses browser applications, Electron applications, cached offline models, and resource-constrained smartphones as deployment examples.
- What you can do after
- Apply it via TensorFlow.js to query an imported Keras model locally in a JavaScript application.
Read how Deep Learning with Python, Third Edition explains TensorFlow.js →
Deep Learning with R, Third Edition
TensorFlow.js is a JavaScript library for running and developing machine-learning models in browsers and JavaScript environments.
- How it is used
- Deploys trained models for inference in browsers and JavaScript applications, including offline and Electron use cases.
- How deep it goes
- Explains API compatibility and model import, but stops short of implementation code or detailed runtime internals.
- Examples
- Uses browser applications, Electron applications, cached models, and resource-constrained devices as deployment examples.
- What you can do after
- Apply it via TensorFlow.js to load a saved Keras model and query predictions from JavaScript.
Read how Deep Learning with R, Third Edition explains TensorFlow.js →
Web Components in Action
TensorFlow.js is a JavaScript library for developing and executing machine-learning models in web browsers and other JavaScript environments.
- How it is used
- Runs a trained hand-recognition model in a browser and embeds its predictions in interactive Web Components.
- How deep it goes
- Explains browser inference and integration, but leaves model-training details largely outside the treatment.
- Examples
- Uses a hand-tracking component, camera video, canvas output, DOM events, and a Web Harp interface.
- What you can do after
- Apply it via Handtrack.js to build a browser hand-tracking component around video input and prediction events.
Related concepts
- JavaScriptuses · JavaScript is a high-level, dynamically typed, multi-paradigm programming language standardized as ECMAScript and used for web and general-purpose programming.
- Kerasimplements · Keras is an open-source, high-level deep-learning API for building, training, evaluating, and deploying neural-network models.
- data modelused by · A data model is a structured representation of data that defines its entities, attributes, relationships, and applicable constraints.
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