## Usage
Hardware-accelerated JavaScript library for machine intelligence
An open-source machine learning framework.
Vanilla JavaScript backend for TensorFlow.js
GPU accelerated WebGL backend for TensorFlow.js
TensorFlow layers API in JavaScript
TensorFlow Data API in JavaScript
Tensorflow model converter for javascript
Invoke scoped data storage for AWS Lambda Node.js Runtime Environment
AWS SDK for JavaScript Lambda Client for Node.js, Browser and React Native
This repository provides native TensorFlow execution in backend JavaScript applications under the Node.js runtime, accelerated by the TensorFlow C binary under the hood. It provides the same API as [TensorFlow.js](https://js.tensorflow.org/api/latest/).
This package adds a WebAssembly backend to TensorFlow.js. It currently supports the following models from our [models](https://github.com/tensorflow/tfjs-models) repo: - BlazeFace - BodyPix - CocoSSD - Face landmarks detection - HandPose - KNN classifier
Detect if your code is running on an AWS Lambda server
OpenTelemetry instrumentation for AWS Lambda function invocations
TypeScript definitions for aws-lambda
Deploy AWS Lambda functions from command line using a json or yaml config file.
The matrix of releases for tfjs-node-lambda.
Lambda client library that supports hybrid tracing in node js
This package adds a GPU accelerated [WebGPU](https://www.w3.org/TR/webgpu/) backend to TensorFlow.js. It currently supports the following models: - BlazeFace - BodyPix - Face landmarks detection - HandPose - MobileNet - PoseDetection - Universal sentence
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Commandline tool and API to run Lambda functions on your local machine.
The logging package for the Powertools for AWS Lambda (TypeScript) library
Canonical list of AWS Lambda runtime identifiers and corresponding CPU architectures
Utilities for in browser visualization with TensorFlow.js