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tensorflow/tensorboard

TensorFlow Visualization Toolkit

GraphCanon updated 3w · GitHub synced 3w

7.2k stars1.7k forksLast push 3w TypeScript Apache-2.0

Decision brief

TensorBoard provides extensive visualization capabilities specifically tailored for TensorFlow projects, aiding in understanding and debugging machine learning experiments.

Good fit when

  • Use TensorBoard when you are working with TensorFlow projects to leverage its specialized plugins for detailed graph visualizations and tensor data insights.
  • Opt for TensorBoard if your project involves complex model architectures or extensive datasets where advanced visualization support is necessary.

Avoid when

  • Avoid TensorBoard if your machine learning setup does not utilize TensorFlow, as it provides limited functionality without a TensorFlow installation.
  • Do not use TensorBoard when your application specifically requires log directory access on Google Cloud Storage, as this feature is absent in environments lacking TensorFlow.
Pricing:
freemium - There is no direct cost associated with using TensorBoard through its open-source version under the Apache 2.0 license.

Observed Jul 16, 2026 · Source: enrich:decision_facts

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Maintenance and security

Full trust report
Maintenance
Very active (4d since push)
As of 3w
Provenance
Not a fork · Organization account
As of 3w
Security (OSV)
No lockfile
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

npm install tensorboard
npm

How it fits your stack(1)

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A tool for providing visualization and dashboard features for machine learning experiments using TensorFlow.

Capability facts

Deploy
Self-host

Source: dockerfile:Dockerfile · Aug 3, 2026

Docker
Dockerfile present

Source: dockerfile:Dockerfile · Aug 3, 2026

MCP server
No MCP server detected

Source: repo_scan · Aug 3, 2026

Languages
typescript, javascript, python

Source: github.language+package.json+pyproject.toml · Aug 3, 2026

Categories

Tags

README

Can I run tensorboard without a TensorFlow installation?

TensorBoard 1.14+ can be run with a reduced feature set if you do not have TensorFlow installed. The primary limitation is that as of 1.14, only the following plugins are supported: scalars, custom scalars, image, audio, graph, projector (partial), distributions, histograms, text, PR curves, mesh. In addition, there is no support for log directories on Google Cloud Storage.

For agents

This page has a .md twin and JSON over the API.

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