# astorfi/TensorFlow-World

:earth_americas: Simple and ready-to-use tutorials for TensorFlow

Repository: https://github.com/astorfi/TensorFlow-World
Canonical: https://ross.abutalabs.com/products/tensorflow-world
Language: Python
License: MIT
License Family: permissive
Topics: deep-learning, neural-network, tensorflow, machine-learning, python, computer-vision
Last push: 2020-12-23T00:18:21+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3449, "days_push": 2080, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4488, forks 405 (observed 2026-08-28T04:08:51.285202+00:00)

## What it is
A collection of simple, ready-to-use tutorials for TensorFlow, each with source code and accompanying documentation hosted in a wiki. It serves as a learning resource for deep learning with TensorFlow.

## Use cases
- learn tensorflow from scratch
- tensorflow tutorials with code examples
- deep learning tutorial repository
- neural network examples in tensorflow
- computer vision tutorials with tensorflow

## When to choose
- you are a beginner wanting structured TensorFlow tutorials
- you prefer learning with runnable source code plus written explanations
- you want MIT-licensed educational material to adapt

## When to avoid
- you need up-to-date coverage of TensorFlow 2.x features
- you want production-ready code rather than teaching examples
- you need actively maintained content (last release 2020)

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, computer-vision
- domain: deep-learning, machine-learning, tutorials, artificial-intelligence
- platform: python
- tags: tensorflow, tutorials, neural-networks, educational

## Member repositories
- astorfi/TensorFlow-World (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:51.285202+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 2026-08-29T18:20:29.460907+00:00, confidence not recorded.
  - readme: https://github.com/astorfi/TensorFlow-World (fetched 2026-08-28T04:08:51.285202+00:00, sha c912b2b05ecf)
- Data as of 2026-08-30T08:39:29.467469+00:00.