Deep Learning
Variants seen in the corpus:
Deep Learningdeep-learning
Providers using this tag (56)
Ranked by API Evangelist rating — Exemplar and Strong are expanded by default.
Strong 2 Solid coverage with minor gaps
Developing 5 Usable, with meaningful gaps to close
Thin 7 Limited public surface area
Emerging 16 Early or largely undocumented
APIs with this tag (8)
Ranked by the provider's API Evangelist rating — the Kin Score is scored per provider, not per API, so every API of a provider shares its band. How the rating works →
Emerging 8 Early or largely undocumented
Apache TVM Python APIThe TVM Python API provides a comprehensive interface for model compilation, optimization, and deployment. ...Riiid Knowledge TracingProprietary deep knowledge tracing and score-prediction models (built on 100M+ student interactions, the Ed...Apache MXNetMXNet provides APIs in Python, Scala, Java, C++, R, Julia, and Perl for deep learning model development, wi...User-friendly Deep Learning (UFDL) APIJSON REST API for the University of Waikato's User-friendly Deep Learning (UFDL) framework, developed by th...HorovodHorovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.Sony Neural Network Libraries (NNabla)NNabla is Sony's open-source deep-learning framework with Python and C++ bindings, dynamic and static compu...Apache MADlibMADlib provides SQL-callable functions for classification, regression, clustering, dimensionality reduction...PyTorch Core APICore PyTorch library for tensor computation and deep learning.
Score breakdown
Frequency
49.0
log-scaled weighted occurrences
Breadth
1.5
spread across providers
Quality lift
21.3
mean composite of providers using it
Cohesion
4.7
strength of nearest seed neighbor
Related tags
MLOps 6 co-occurrences
Inference 8 co-occurrences
Computer-Vision 12 co-occurrences
Edge Computing 5 co-occurrences
Machine-Learning 36 co-occurrences
Models 7 co-occurrences
Python 7 co-occurrences
Semiconductors 6 co-occurrences
Where this tag comes from
Provider tag52
Api tag8
Cohort brief
Auto-generatedThe 56 providers in the APIs.io catalog tagged Deep Learning, scored on the Kin Score. Every figure below is computed from the catalog — nothing here is written.
Providers
56
all scored
Mean Kin Score
18
-2.7 vs catalog 20.7
Mean Agent Readiness
7.2
-2.5 vs catalog 9.7
Spread
2.8–60.2
median 11.7 · σ 15.3
How the 56 split by band
Exemplar 0Strong 2Developing 5Thin 7Emerging 16Minimal 26
Facet averages, against the whole catalog
| Facet | This cohort | Catalog | Difference | Scored |
|---|---|---|---|---|
| Operational Transparency | 11.6 | 11.3 | +0.3 | 56 |
| Contract Governance | 6 | 6.4 | -0.4 | 56 |
| Developer Ergonomics | 16.9 | 17.9 | -1 | 56 |
| Discoverability | 57.5 | 60.4 | -2.9 | 56 |
| Contract Quality | 13.6 | 17.5 | -3.9 | 56 |
| Access Clarity | 17.4 | 22.3 | -4.9 | 56 |
A facet is averaged over the members that carry it, not over the whole cohort — the “Scored” column is that count. Averaging an absent facet as zero would score our own coverage gaps as the providers’ posture.
What this cohort publishes
| Artifact | This cohort | Catalog | Difference |
|---|---|---|---|
| MCP server (any) | 9% | 16% | -7 |
| MCP server (first-party) | 5% | 7% | -2 |
| Agent Skills | 0% | 0% | 0 |
| OAuth scopes | 4% | 9% | -5 |
| Security | 86% | 88% | -2 |
| Arazzo workflows | 4% | 2% | +2 |
| Governance rules | 18% | 13% | +5 |
mcp_pct counts any mcp/ artifact including ones API Evangelist derived from the provider OpenAPI; mcp_first_party_pct counts only servers the provider publishes. Prefer the latter.
Top by Kin Score
- 1 Paperspace 60.2
- 2 Amazon Rekognition 55.4
- 3 DeepL 49.9
- 4 Lambda 49.3
- 5 RTB House 46.6
- 6 Hugging Face Transformers 45.3
- 7 BigML 44.9
- 8 TensorFlow 38.2
- 9 Activeloop 37.4
- 10 Google TensorFlow 33.9
Top by Agent Readiness
- 1 Hugging Face Transformers 53.9
- 2 Amazon Rekognition 36.2
- 3 Deep Instinct 30.2
- 4 RTB House 26.1
- 5 TensorFlow 25.5
- 6 Triton Inference Server 25.5
- 7 Kubeflow 23.2
- 8 Paperspace 22.8
- 9 Lambda 22.3
- 10 DeepL 20.9
All 56 members of this roster resolve to a scored provider in
the catalog.Generated from the catalog build of
25 August 2026, across 26891
providers, using the same computation served by the
APIs.io cohort API. Briefs are published for rosters of
5 or more scored providers; below that a distribution is not meaningful.
Work with this as data
Every tag here is available over the APIs.io API and to AI agents over MCP.
MCP server
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https://apis.io/mcp
Tools for tags
7 MCP tools reach this
find_tagsBrowse and filter every tag in the catalog.get_cohortThis tag as a scored cohort — every provider carrying it, with scores.cohort_statsPRO — the distribution across this tag: mean, median, band split, adoption rates.cohort_rankingsPRO — the leaderboard, on composite AND agent-readiness axes.apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.resolveTurn a domain, URL or GitHub org into the provider it belongs to.find_cohortsEvery scored population of providers in the catalog.
Call it yourself
curl for this page
This tag
curl "https://apis.io/api/v1/tags/deep-learning"
All tags
curl "https://apis.io/api/v1/tags?limit=25"
As a scored cohort
curl "https://apis.io/api/v1/cohorts/tag/deep-learning"
The distribution (Pro)
curl "https://apis.io/api/v1/cohorts/tag/deep-learning/stats" \
-H "X-API-Key: $APIS_IO_KEY"Discovery needs no key. Ratings and market analysis are Pro.