# Netflix/vectorflow

Repository: https://github.com/Netflix/vectorflow
Canonical: https://ross.abutalabs.com/products/vectorflow
Language: D
License: Apache-2.0
License Family: permissive
Last push: 2024-05-02T18:52:43+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": 3319, "days_push": 853, "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 1294, forks 88 (observed 2026-08-28T04:04:16.280826+00:00)

## What it is
Vectorflow is a minimalist neural network library written in D, optimized for sparse data and single-machine training environments. It is distributed as a dub package and requires only a D compiler with no external dependencies.

## Use cases
- train neural networks on sparse data
- run logistic regression on text datasets like RCV1
- build lightweight ML models without GPU clusters
- experiment with deep learning in the D language
- train embeddings on a single machine

## When to choose
- your data is sparse and fits on a single machine
- you want a dependency-free, minimalist neural net library
- you work in the D ecosystem and want fast LDC-compiled training

## When to avoid
- you need distributed or multi-GPU training
- you need a large ecosystem of pretrained models and tooling
- your team does not use the D language

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: machine-learning
- platform: cross-platform
- tags: neural-networks, sparse-data, d-language, single-machine, algorithms, linux, macos

## Member repositories
- Netflix/vectorflow (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:16.280826+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 2026-08-30T04:54:03.555783+00:00, confidence not recorded.
  - readme: https://github.com/Netflix/vectorflow (fetched 2026-08-28T04:04:16.280826+00:00, sha 376cea20acc5)
- Data as of 2026-08-30T08:39:29.467469+00:00.