# kennethleungty/Neural-Network-Architecture-Diagrams

Diagrams for visualizing neural network architecture

Repository: https://github.com/kennethleungty/Neural-Network-Architecture-Diagrams
Canonical: https://ross.abutalabs.com/products/neural-network-architecture-diagrams
Homepage: https://towardsdatascience.com/how-to-easily-draw-neural-network-architecture-diagrams-a6b6138ed875
License: MIT
License Family: permissive
Topics: neural-network, architecture, visualization, visualisation, diagrams, cnn, deep-learning, artificial-intelligence, artificial-neural-networks, networks, deep-neural-networks, rnn
Last push: 2025-04-12T16:09:36+00:00

## Health v2 (maintenance only)
Score: 39/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 16, release rhythm 35, longevity 100
- inputs: {"age_days": 1839, "days_push": 508, "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 1173, forks 528 (observed 2026-08-28T04:03:51.888666+00:00)

## What it is
A curated collection of neural network architecture diagrams (CNNs, RNNs, autoencoders, U-Net, YOLO, etc.) created with the no-code diagrams.net tool, with editable source files. It accompanies a Towards Data Science tutorial on drawing architecture diagrams yourself.

## Use cases
- draw neural network architecture diagrams
- visualize CNN model architecture
- create diagrams for deep learning models
- find editable diagram templates for neural networks
- explain model architecture to non-technical audiences
- learn to use diagrams.net for ML diagrams

## When to choose
- you want ready-made, editable diagram templates for common architectures like VGG-16, U-Net, or YOLO
- you prefer a no-code drag-and-drop approach over code-generated diagrams
- you need visuals for papers, presentations, or blog posts about model architectures

## When to avoid
- you want to auto-generate diagrams programmatically from model code (e.g., from Keras or PyTorch)
- you need a library or CLI tool rather than a gallery of example files
- you need diagrams for architectures not covered by the existing examples

## Facets
- artifact type: learning-resource
- maturity: stable
- function: data-visualization, developer-tools
- domain: deep-learning, machine-learning, artificial-intelligence, tutorials, data-visualization
- platform: cross-platform
- tags: diagrams, drawio, neural-network-diagrams, no-code, model-architecture, examples-gallery, web-server

## Member repositories
- kennethleungty/Neural-Network-Architecture-Diagrams (main) score 39

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:51.888666+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 2026-08-30T06:28:23.276422+00:00, confidence not recorded.
  - readme: https://github.com/kennethleungty/Neural-Network-Architecture-Diagrams (fetched 2026-08-28T04:03:51.888666+00:00, sha 3c27424e95a8)
  - homepage: https://towardsdatascience.com/how-to-easily-draw-neural-network-architecture-diagrams-a6b6138ed875 (fetched 2026-08-29T12:33:57.852118+00:00, sha e75727d15637)
  - site_page: https://towardsdatascience.com/about-towards-data-science-d691af11cc2f (fetched 2026-08-29T12:33:57.861872+00:00, sha bf7749ccc92b)
- Data as of 2026-08-30T08:39:29.467469+00:00.