# tensorflow/tensorboard

TensorFlow's Visualization Toolkit

Repository: https://github.com/tensorflow/tensorboard
Canonical: https://ross.abutalabs.com/products/tensorboard
Language: TypeScript
License: Apache-2.0
License Family: permissive
Last push: 2026-08-24T23:20:33+00:00

## Health v2 (maintenance only)
Score: 88/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 66, longevity 100
- inputs: {"age_days": 3397, "days_push": 9, "days_rel": 65, "gap_med": 155, "n_releases_24m": 4}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 7206, forks 1712 (observed 2026-08-28T04:09:56.612739+00:00)

## What it is
TensorBoard is TensorFlow's visualization toolkit, a suite of web applications for inspecting and understanding machine learning training runs, graphs, and metrics. It runs locally as a web server that reads summary event logs from a log directory and renders interactive dashboards in the browser.

## Use cases
- visualize training loss and accuracy curves
- inspect neural network computation graphs
- compare hyperparameter tuning experiments
- debug model embeddings with projection visualizations
- view image and audio summaries from training runs
- monitor ML experiments offline behind a firewall

## When to choose
- you train models with TensorFlow or Keras and need built-in visualization
- you want a free, offline, self-hosted experiment dashboard
- you need to inspect computation graphs and profiling data from TF runs

## When to avoid
- you use PyTorch exclusively and prefer native tooling like Weights & Biases
- you need cloud-hosted, collaborative experiment tracking
- you need real-time production model monitoring rather than training-time visualization

## Facets
- artifact type: application
- maturity: active
- function: data-visualization, monitoring, http-server
- domain: machine-learning, deep-learning, data-visualization, developer-tools
- platform: python, cross-platform, cli
- tags: tensorflow, experiment-tracking, training-metrics, dashboards, web-applications, web-server

## Member repositories
- tensorflow/tensorboard (main) score 88

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:56.612739+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:39:51.227215+00:00, confidence not recorded.
  - readme: https://github.com/tensorflow/tensorboard (fetched 2026-08-28T04:09:56.612739+00:00, sha d67c2854ae0c)
- Data as of 2026-08-30T08:39:29.467469+00:00.