# martin-gorner/tensorflow-mnist-tutorial

Sample code for "Tensorflow and deep learning, without a PhD" presentation and code lab.

Repository: https://github.com/martin-gorner/tensorflow-mnist-tutorial
Canonical: https://ross.abutalabs.com/products/tensorflow-mnist-tutorial
License Family: other
Archived: true
Last push: 2018-05-18T18:48:00+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3768, "days_push": 3029, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1432, forks 653 (observed 2026-08-28T04:04:43.059527+00:00)

## What it is
Sample code accompanying the 'TensorFlow and deep learning, without a PhD' presentation and code lab, teaching neural network basics on the MNIST handwritten digit dataset. The repository has been moved to GoogleCloudPlatform/tensorflow-without-a-phd and is no longer maintained here.

## Use cases
- learn deep learning basics with mnist
- follow the tensorflow without a phd codelab
- example code for training a neural network on handwritten digits
- introductory tensorflow tutorial exercises
- understand how a simple neural net is built step by step

## When to choose
- you are following the 'TensorFlow and deep learning, without a PhD' talk or lab
- you want a gentle, step-by-step introduction to neural networks using MNIST

## When to avoid
- you need actively maintained or modern TensorFlow 2.x code
- you want production-ready machine learning code
- you need a supported release or license

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: machine-learning, deep-learning
- domain: machine-learning, deep-learning, tutorials
- platform: python, cross-platform
- tags: mnist, tensorflow, educational, code-lab, neural-networks, moved-repository

## Member repositories
- martin-gorner/tensorflow-mnist-tutorial (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:43.059527+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 2026-08-30T04:37:02.495770+00:00, confidence not recorded.
  - readme: https://github.com/martin-gorner/tensorflow-mnist-tutorial (fetched 2026-08-28T04:04:43.059527+00:00, sha 525ce0a46b74)
- Data as of 2026-08-30T08:39:29.467469+00:00.