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With Humanity alternatives & similar sites

Evan Freed — AI and Machine 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
aayushgautam.tech ↗	73 match 2 shared topics	Aayush Gautam - AI & Machine Learning Developer	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
regulateaiml.com ↗	72 match 2 shared topics	Latest Insights in AI and Machine Learning Developments \| regulateaiml	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
abdullahibnshahin.com ↗	72 match 2 shared topics	Software & Machine Learning Engineer \| Abdullah	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
tensorboard.com ↗	72 match 2 shared topics	ApX Machine Learning	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
airaft.org ↗	72 match 2 shared topics	AIRaft - Expert guides on machine learning concepts and techniques	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
ml-cfd.com ↗	72 match 2 shared topics	ML-CFD \| Blog about machine learning and computational fluid dynamics	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
regulargeek.com ↗	71 match 2 shared topics	Regular Geek – A mix of software development, processes, machine learning and data.	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
mlbridge.net ↗	71 match 2 shared topics	ML Bridge - Decentralized Machine Learning Infrastructure	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
mlsensors.org ↗	71 match 2 shared topics	Machine Learning Sensors - MLSensors	en	technology-and-computing	robotsllmsaihumans	emailphone	none
deepinfra.ai ↗	71 match 2 shared topics	Machine Learning Models and Infrastructure \| DeepInfra	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
deepinfra.com ↗	71 match 2 shared topics	Machine Learning Models and Infrastructure \| DeepInfra	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
mlcompassguide.dev ↗	71 match 2 shared topics	ML Compass Guide: Learn Machine Learning Algorithms	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
wil725.com ↗	70 match 2 shared topics	AI & Data Science Projects by Will \|Gen AI and ML cases	en	artificial-intelligence Ghost	robotsllmsaihumans	emailphone	none
deepanshumody.com ↗	70 match 2 shared topics	Deepanshu Mody \| Machine Learning Research Engineer	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
alexrudy.net ↗	70 match 2 shared topics	Alex Rudy \| This is my home page, and a landing for a few personal projects. Professionally, I work on the Machine Learning Platform for Discord.	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 1
emlwr.org ↗	70 match 2 shared topics	Efficient Machine Learning with R	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
aadityachapagain.com ↗	70 match 2 shared topics	Aaditya Chapagain \| Machine Learning Engineer & Full Stack Developer	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
win.ai ↗	70 match 2 shared topics	Artificial Intelligence Explained: AI Tools, Machine Learning & Guides	en	artificial-intelligence WordPress	robots llmsaihumans	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.