# tflearn/tflearn

Deep learning library featuring a higher-level API for TensorFlow.

Repository: https://github.com/tflearn/tflearn
Canonical: https://ross.abutalabs.com/products/tflearn
Homepage: http://tflearn.org
Language: Python
License: NOASSERTION
License Family: other
Topics: tflearn, tensorflow, neural-network, deep-learning, machine-learning, data-science
Last push: 2024-05-06T11:34:20+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3807, "days_push": 849, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 9576, forks 2355 (observed 2026-08-28T04:10:35.884198+00:00)

## What it is
TFLearn is a modular deep learning library providing a higher-level, Keras-like API on top of TensorFlow for building and training neural networks. It offers built-in layers, optimizers, regularizers, and helpers for fast prototyping while remaining transparent to underlying TensorFlow graphs.

## Use cases
- build and train neural networks with a simple high-level API
- prototype CNN, LSTM, or ResNet models quickly
- train a TensorFlow graph with multiple inputs and outputs
- visualize network weights, gradients, and activations
- generate sequences with a trained LSTM model
- run training across multiple CPUs or GPUs

## When to choose
- you want a simpler API than raw TensorFlow for deep learning experiments
- you are maintaining or studying legacy codebases built on TFLearn
- you need quick prototyping of classic architectures like CNNs and RNNs on TensorFlow 2.x

## When to avoid
- you are starting a new project - Keras (tf.keras) is the actively maintained high-level TensorFlow API
- you need cutting-edge deep learning features or active community support
- you require compatibility with the latest TensorFlow releases or modern ecosystem tooling

## Facets
- artifact type: library
- maturity: maintenance
- function: deep-learning, machine-learning, llm-training
- domain: deep-learning, machine-learning, data-science
- platform: python, windows
- tags: tensorflow, neural-networks, high-level-api, keras-alternative, legacy, linux, macos, gpu

## Member repositories
- tflearn/tflearn (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:35.884198+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 2026-08-29T17:21:55.716235+00:00, confidence not recorded.
  - readme: https://github.com/tflearn/tflearn (fetched 2026-08-28T04:10:35.884198+00:00, sha 94cf22b073fe)
  - homepage: http://tflearn.org (fetched 2026-08-29T08:21:32.238334+00:00, sha 1877c8ee407e)
  - site_page: http://tflearn.org/installation (fetched 2026-08-29T08:21:32.248472+00:00, sha a3314b6c85e4)
  - registry_pypi: https://pypi.org/pypi/tflearn/json (fetched 2026-08-29T08:21:32.253168+00:00, sha 99d4207b257a)
  - site_page: http://tflearn.org/doc_index (fetched 2026-08-29T08:21:32.250768+00:00, sha 2572db3c17ef)
- Data as of 2026-08-30T08:39:29.467469+00:00.