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Sites similar to ml-cfd.com

Ml Cfd alternatives & similar sites

ML-CFD | Blog about machine learning and computational fluid dynamics — 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 →

DomainMatchTitleCountry/LangCategoryAI filesContactAI-protection
deepdivision.net 74 match
2 shared topics
Deep Division | Deep Division is blog about Deep Learning, Machine Learning, programming and mathematics. en artificial-intelligence robotsllmsaihumans emailphone none
programmathically.com 73 match
2 shared topics
Programmathically - A Blog on Building Machine Learning Solutions en artificial-intelligenceWordPress robotsllmsaihumans emailphone none
amaboh.com 71 match
2 shared topics
Amaboh Achu - Machine Learning and data engineering portfolio en artificial-intelligence robotsllmsaihumans emailphone none
situnayake.com 71 match
2 shared topics
Daniel Situnayake’s blog | My thoughts on embedded machine learning. en artificial-intelligence robotsllmsaihumans emailphone none
aayushgautam.tech 71 match
2 shared topics
Aayush Gautam - AI & Machine Learning Developer en artificial-intelligence robotsllmsaihumans emailphone none
1chipml.org 69 match
2 shared topics
GitHub - 1chipML/1chipML: a library for numerical crunching and machine learning on microcontrollers · GitHub en artificial-intelligence robotsllmsaihumans emailphone none
aadityachapagain.com 69 match
2 shared topics
Aaditya Chapagain | Machine Learning Engineer & Full Stack Developer en artificial-intelligence robotsllmsaihumans emailphone none
deepinfra.ai 69 match
2 shared topics
Machine Learning Models and Infrastructure | DeepInfra en artificial-intelligence robotsllmsaihumans emailphone none
deepinfra.com 69 match
2 shared topics
Machine Learning Models and Infrastructure | DeepInfra en artificial-intelligence robotsllmsaihumans emailphone none
deepanshumody.com 69 match
2 shared topics
Deepanshu Mody | Machine Learning Research Engineer en artificial-intelligence robotsllmsaihumans emailphone none
debuggercafe.com 69 match
2 shared topics
DebuggerCafe - Deep Learning, Machine Learning, Artificial Intelligence en artificial-intelligenceWordPressWooCommerce robotsllmsaihumans emailphone none
kevinchow.org 68 match
2 shared topics
Kevin Chow's Blog – My journey of machine learning and data science. en artificial-intelligenceWordPress robotsllmsaihumans emailphone none
nadesri.com 68 match
2 shared topics
Nade's Notes – Hello there! Here I talk about stuff I like, including Natural Language Processing, Machine Learning, & Software Engineering :) en artificial-intelligenceWordPress robotsllmsaihumans emailphone none
jvanzyl.com 68 match
2 shared topics
Jay van Zyl @ ecosystem.Ai – Predictive technology: computational social science en technology-and-computingWordPressWooCommerce robotsllmsaihumans emailphone none
dendisuhubdy.com 68 match
2 shared topics
Adventures and Amusings of a Mathematician en artificial-intelligence robotsllmsaihumans emailphone partial · 8
pro-datascience.com 68 match
2 shared topics
Zero Code AI Enabled Machine Learning Model Development tools en technology-and-computingWordPressWooCommerce robotsllmsaihumans emailphone none
deep-learning-mastery.com 67 match
2 shared topics
Tobias Klein Machine Learning Engineer Portfolio en artificial-intelligence robotsllmsaihumans emailphone none
iamchaichai.com 67 match
2 shared topics
Life and Code - The never-ending journey of learning and growth in software development en artificial-intelligenceWordPress 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:

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.