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Deep Learning Gallery - a curated list of awesome deep learning projects — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Artificial Intelligence →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
1cognition.com ↗	70 match 1 shared topics	1 Cognition - Deep Learning Visualized	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
rastervision.io ↗	69 match 1 shared topics	Raster Vision: An open-source machine learning library for deep learning on satellite and aerial imagery	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
rachelchiong.com ↗	69 match 1 shared topics	Rachel’s Blog \| This is Rachel’s blog - containing learnings from ELEC4630 - Computer Vision and Deep Learning	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
charlie-arsenec.com ↗	69 match 1 shared topics	Charles-André Arsenec \| Machine Learning & Data Science Projects	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
100aiprojects.dev ↗	68 match 1 shared topics	100 AI Projects - AI Development Portfolio	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
aslam.ai ↗	68 match 1 shared topics	Aslam.ai - The Worlds Best Curated List of Ai Tools	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
pete.com ↗	68 match 1 shared topics	PETE Learning - Elevate training. Optimize learning.	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
ocandocrypto.com ↗	68 match 1 shared topics	Learning in Public: AI, DeFi & Economics learnings.	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
mikeyh.com ↗	68 match 1 shared topics	Michael Hsu \| Projects, Thoughts & Learning	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
ashfieldexcellenceacademy.com ↗	67 match 1 shared topics	Home \| Nazaré \| Strategic Learning Partner	UK~ en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
pharmaexcellenceacademy.com ↗	67 match 1 shared topics	Home \| Nazaré \| Strategic Learning Partner	UK~ en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
pharmamarketingacademy.com ↗	67 match 1 shared topics	Home \| Nazaré \| Strategic Learning Partner	UK~ en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
pharmaknowledgeacademy.com ↗	67 match 1 shared topics	Home \| Nazaré \| Strategic Learning Partner	UK~ en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
pharmaskillsacademy.com ↗	67 match 1 shared topics	Home \| Nazaré \| Strategic Learning Partner	UK~ en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
qengineering.eu ↗	66 match 1 shared topics	All the machine vision and deep learning solutions. - Q-engineering	European Union en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
guidobiosca.com ↗	66 match 1 shared topics	Guido Biosca \| Machine Learning Engineer	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
phyloflo.com ↗	66 match 1 shared topics	Phyloflo - AI-Native Scientific Computing Platform \| Geometric Deep Learning for Omics Analysis	United States~ en	artificial-intelligence	robotsllmsaihumans	email phone	none
qstream-quest.com ↗	66 match 1 shared topics	Qstream AI-powered microlearning \| Transform Workplace Learning	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.