# adeshpande3/Tensorflow-Programs-and-Tutorials

Implementations of CNNs, RNNs, GANs, etc

Repository: https://github.com/adeshpande3/Tensorflow-Programs-and-Tutorials
Canonical: https://ross.abutalabs.com/products/tensorflow-programs-and-tutorials
Language: Jupyter Notebook
License Family: other
Topics: tensorflow, deep-learning, machine-learning
Last push: 2018-06-12T19:03:58+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3554, "days_push": 3004, "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 1055, forks 316 (observed 2026-08-28T04:03:24.167793+00:00)

## What it is
A collection of Jupyter Notebook tutorials implementing popular deep learning concepts like CNNs, RNNs, and GANs in TensorFlow. It also includes experiments reproducing ideas from recent research papers.

## Use cases
- learn how to implement a CNN in TensorFlow
- understand how GANs work with code examples
- train a character-level RNN for text generation
- study how noisy labels affect CNN training
- get started with TensorFlow deep learning tutorials
- see linear and logistic regression implemented in TensorFlow

## When to choose
- you are learning deep learning fundamentals through hands-on notebooks
- you want readable TensorFlow 1.x-style implementations of classic models
- you want paper-inspired experiments explained step by step

## When to avoid
- you need production-ready or maintained TensorFlow 2.x code
- you need a library or framework to depend on rather than educational notebooks
- you need up-to-date best practices, as the repo has not been updated since 2018

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

## Member repositories
- adeshpande3/Tensorflow-Programs-and-Tutorials (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:24.167793+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 2026-08-30T06:58:29.047635+00:00, confidence not recorded.
  - readme: https://github.com/adeshpande3/Tensorflow-Programs-and-Tutorials (fetched 2026-08-28T04:03:24.167793+00:00, sha a48de2a02dc8)
- Data as of 2026-08-30T08:39:29.467469+00:00.