# alrojo/tensorflow-tutorial

Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE

Repository: https://github.com/alrojo/tensorflow-tutorial
Canonical: https://ross.abutalabs.com/products/alrojo-tensorflow-tutorial
Language: Jupyter Notebook
License Family: other
Last push: 2016-11-04T15:00:06+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3688, "days_push": 3589, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1955, forks 439 (observed 2026-08-28T04:05:58.995305+00:00)

## What it is
A collection of five interactive Jupyter notebook labs teaching deep learning with TensorFlow, covering feedforward networks, CNNs, RNNs, autoencoders, and a Kaggle competition. Originally used in an Nvidia-sponsored deep learning course in London.

## Use cases
- learn tensorflow from scratch
- hands-on deep learning tutorials with jupyter notebooks
- understand feedforward neural networks on mnist
- learn convolutional neural networks for image classification
- build encoder-decoder rnn models for translation
- practice for a kaggle competition
- learn autoencoders for unsupervised learning

## When to choose
- you want interactive notebook-based deep learning exercises runnable on a laptop CPU
- you are a beginner learning TensorFlow through examples and visualizations
- you want course-style labs covering FFN, CNN, RNN, and autoencoders

## When to avoid
- you need up-to-date TensorFlow 2.x or modern APIs since the material dates from 2016
- you need production-ready code or a maintained library
- you need a license permitting reuse of the material

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: machine-learning, deep-learning
- domain: deep-learning, tutorials, machine-learning
- platform: python, cross-platform
- tags: tensorflow, jupyter-notebooks, deep-learning-course, kaggle, mnist, cnn, rnn, autoencoder, educational

## Member repositories
- alrojo/tensorflow-tutorial (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:58.995305+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 2026-08-30T03:06:26.281218+00:00, confidence not recorded.
  - readme: https://github.com/alrojo/tensorflow-tutorial (fetched 2026-08-28T04:05:58.995305+00:00, sha 584842d66130)
- Data as of 2026-08-30T08:39:29.467469+00:00.