# google/automl

Google Brain AutoML

Repository: https://github.com/google/automl
Canonical: https://ross.abutalabs.com/products/automl
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Topics: automl, efficientdet, object-detection, efficientnet, efficientnetv2
Archived: true
Last push: 2025-03-02T07:46:39+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 9, release rhythm 8, longevity 100
- inputs: {"age_days": 2365, "days_push": 549, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6474, forks 1464 (observed 2026-08-28T04:09:43.720874+00:00)

## What it is
Google Brain's AutoML repository containing implementations of AutoML models and libraries such as EfficientNet, EfficientNetV2, and EfficientDet. It provides reference code for state-of-the-art image classification and object detection architectures.

## Use cases
- train image classification models with efficientnet
- run object detection with efficientdet
- implement efficientnetv2 in my project
- reproduce google brain automl research models
- fine-tune pretrained efficientnet checkpoints

## When to choose
- you need reference implementations of EfficientNet/EfficientDet family models
- you want pretrained checkpoints for image classification or detection
- you're doing computer vision research based on Google Brain AutoML work

## When to avoid
- you need a general-purpose AutoML platform with automated hyperparameter search
- you work outside Python/TensorFlow ecosystems
- you need production serving infrastructure rather than model code

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, image-processing, computer-vision
- domain: machine-learning, computer-vision, deep-learning, artificial-intelligence
- platform: python, cross-platform
- tags: automl, efficientnet, efficientdet, object-detection, image-classification, google-brain, tensorflow, gpu

## Member repositories
- google/automl (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:43.720874+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 2026-08-29T17:44:35.400018+00:00, confidence not recorded.
  - readme: https://github.com/google/automl (fetched 2026-08-28T04:09:43.720874+00:00, sha 683a62be33e6)
- Data as of 2026-08-30T08:39:29.467469+00:00.