# AlexiaJM/Deep-learning-with-cats

Deep learning with cats (^._.^)

Repository: https://github.com/AlexiaJM/Deep-learning-with-cats
Canonical: https://ross.abutalabs.com/products/deep-learning-with-cats
Language: Python
License: GPL-3.0
License Family: copyleft
Topics: deep-learning, cat, cuda, gan, picture
Last push: 2020-05-16T11:01:56+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": 3372, "days_push": 2300, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1440, forks 186 (observed 2026-08-28T04:04:44.196885+00:00)

## What it is
A toy educational repository demonstrating how to build deep neural networks, primarily Generative Adversarial Networks (DCGAN, WGAN, WGAN-GP, LSGAN) to generate cat images, plus neural style transfer with CycleGAN and fast neural style. It is written in Python with PyTorch and serves as a learning resource for GAN experimentation.

## Use cases
- learn how to implement GANs from scratch
- generate images of cats with DCGAN
- compare WGAN, WGAN-GP, and LSGAN loss functions
- apply neural style transfer to photos
- get started with PyTorch deep learning projects
- experiment with GAN training tricks like noisy labels

## When to choose
- you want readable, minimal GAN code for learning purposes
- you need simple reference implementations of DCGAN, WGAN, WGAN-GP, or LSGAN in PyTorch
- you want a fun starter project for image generation

## When to avoid
- you need production-ready or actively maintained GAN code
- you want the latest GAN features like spectral normalization or relativistic losses
- you need a supported library with releases and bug fixes

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: deep-learning, machine-learning, image-processing
- domain: deep-learning, machine-learning, image-processing
- platform: python
- tags: gan, pytorch, generative-models, educational, cats, style-transfer, dcgan, wgan, gpu

## Member repositories
- AlexiaJM/Deep-learning-with-cats (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:44.196885+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 2026-08-30T04:36:30.218338+00:00, confidence not recorded.
  - readme: https://github.com/AlexiaJM/Deep-learning-with-cats (fetched 2026-08-28T04:04:44.196885+00:00, sha 7e32520e6c3d)
- Data as of 2026-08-30T08:39:29.467469+00:00.