Predict linear relationships between numbers
Detect bank fraud without revealing personal data
Make RAG evaluation dataset. 100% compatible to AutoRAG
Monitor application health
Display a welcome message on a webpage
Explore income data with an interactive visualization tool
Display and analyze PyTorch Image Models leaderboard
Submit evaluations for speaker tagging and view leaderboard
Explore and filter model evaluation results
Explore token probability distributions with sliders
Display color charts and diagrams
Multilingual metrics for the LMSys Arena Leaderboard
Analyze and compare datasets, upload reports to Hugging Face
Tfjs is a JavaScript library designed for data visualization and machine learning tasks in the browser. It is particularly focused on predicting linear relationships between numbers and is part of the TensorFlow.js ecosystem, which allows developers to run machine learning models in the browser or in Node.js. Tfjs provides tools for visualizing data and model predictions, making it easier to understand and interpret results.
• Integration with TensorFlow.js: Tfjs works seamlessly with TensorFlow.js, enabling visualization of machine learning models and data. • Data Visualization: Provides tools to create interactive and dynamic visualizations of data. • Real-time Updates: Supports real-time updates for dashboards and visualizations. • Cross-platform Compatibility: Can be used in both browser-based and Node.js environments. • Extensive Customization: Allows developers to customize visualizations using D3.js and other libraries.
npm install @tensorflow/tfjs
import * as tf from '@tensorflow/tfjs';
What is Tfjs primarily used for?
Tfjs is primarily used for data visualization and machine learning tasks in the browser. It is particularly useful for visualizing data and model predictions.
Is Tfjs part of TensorFlow.js?
Yes, Tfjs is part of the TensorFlow.js ecosystem and is designed to work seamlessly with TensorFlow.js models and data.
Can Tfjs be used for real-time data visualization?
Yes, Tfjs supports real-time updates, making it suitable for applications that require dynamic and interactive visualizations.