#clustering — Public Fediverse posts

https://www.europesays.com/ie/457128/ MCP in the Java World: Bringing Architectural Strategy to LLM Integrations #AI #AIDevelopment #ArtificialIntelligence #Arts #ArtsAndDesign #ArtsAndDesign #ArtsDesign #Caching #Clustering&Caching #CodeGeneration #Design #Development #DistributedCache #Éire #Entertainment #IE #Infrastructure #Ireland #Java #LargeLanguageModels #McpJavaArchitecturalStrategyLlmIntegrations #Memcached #ML&DataEngineering #performance

Pin Clustering in .NET MAUI Maps
https://devblogs.microsoft.com/dotnet/pin-clustering-in-dotnet-maui-maps/

#microsoft #NET #NET_MAUI #NET_11 #clustering #controls #maps #mobile

Pin Clustering in .NET MAUI Maps
https://devblogs.microsoft.com/dotnet/pin-clustering-in-dotnet-maui-maps/

#microsoft #NET #NET_MAUI #NET_11 #clustering #controls #maps #mobile

Pin Clustering in .NET MAUI Maps
https://devblogs.microsoft.com/dotnet/pin-clustering-in-dotnet-maui-maps/

#microsoft #NET #NET_MAUI #NET_11 #clustering #controls #maps #mobile

From the .NET blog...

In case you missed it earlier...

Pin Clustering in .NET MAUI Maps
https://devblogs.microsoft.com/dotnet/pin-clustering-in-dotnet-maui-maps/ #dotnet #NETMAUI #NET11 #clustering #controls #maps #mobile

From the .NET blog...

In case you missed it earlier...

Pin Clustering in .NET MAUI Maps
https://devblogs.microsoft.com/dotnet/pin-clustering-in-dotnet-maui-maps/ #dotnet #NETMAUI #NET11 #clustering #controls #maps #mobile

From the .NET blog...

In case you missed it earlier...

Pin Clustering in .NET MAUI Maps
https://devblogs.microsoft.com/dotnet/pin-clustering-in-dotnet-maui-maps/ #dotnet #NETMAUI #NET11 #clustering #controls #maps #mobile

From the .NET blog...

In case you missed it earlier...

Pin Clustering in .NET MAUI Maps
https://devblogs.microsoft.com/dotnet/pin-clustering-in-dotnet-maui-maps/ #dotnet #NETMAUI #NET11 #clustering #controls #maps #mobile

Pin Clustering in .NET MAUI Maps
https://devblogs.microsoft.com/dotnet/pin-clustering-in-dotnet-maui-maps/

#microsoft #NET #NET_MAUI #NET_11 #clustering #controls #maps #mobile

Pin Clustering in .NET MAUI Maps
https://devblogs.microsoft.com/dotnet/pin-clustering-in-dotnet-maui-maps/

#microsoft #NET #NET_MAUI #NET_11 #clustering #controls #maps #mobile

Pin Clustering in .NET MAUI Maps
https://devblogs.microsoft.com/dotnet/pin-clustering-in-dotnet-maui-maps/

#microsoft #NET #NET_MAUI #NET_11 #clustering #controls #maps #mobile

From the .NET blog...

Pin Clustering in .NET MAUI Maps
https://devblogs.microsoft.com/dotnet/pin-clustering-in-dotnet-maui-maps/ #dotnet #NETMAUI #NET11 #clustering #controls #maps #mobile

Spatiotemporal #clustering of highly pathogenic avian #influenza (HPAI) #H5N1 at the wild #waterfowl - #poultry interface: Vector-specific #spillover risks in the #US, 2022–2025, https://etidiohnew.blogspot.com/2026/03/spatiotemporal-clustering-of-highly.html

#MAC #TríTuệNhiệt #Thunderbolt #GộpServer Clustering Mac Mini (Thunderbolt 4) có thể chậm 10x nhưng Thunderbolt 5+RDMA hứa hẹn tăng tốc 2x. Tối ưu hóa cluster phi chính thức (non-RDMA) đang được phát triển, phù hợp cho người sở hữu Mac base model. Tìm hiểu phần mềm mới & kiến thức về phân phối mô hình LLM. #CôngNghệ #AI #Optimize

*(#MAC #AI #Thunderbolt #Clustering Clustering Thunderbolt-4 Macs may incur 10x slowdown, but Thunderbolt-5 RDMA clusters boost speed 2x. Unofficial optimizations for

#MAC #TríTuệNhiệt #Thunderbolt #GộpServer Clustering Mac Mini (Thunderbolt 4) có thể chậm 10x nhưng Thunderbolt 5+RDMA hứa hẹn tăng tốc 2x. Tối ưu hóa cluster phi chính thức (non-RDMA) đang được phát triển, phù hợp cho người sở hữu Mac base model. Tìm hiểu phần mềm mới & kiến thức về phân phối mô hình LLM. #CôngNghệ #AI #Optimize

*(#MAC #AI #Thunderbolt #Clustering Clustering Thunderbolt-4 Macs may incur 10x slowdown, but Thunderbolt-5 RDMA clusters boost speed 2x. Unofficial optimizations for

#MAC #TríTuệNhiệt #Thunderbolt #GộpServer Clustering Mac Mini (Thunderbolt 4) có thể chậm 10x nhưng Thunderbolt 5+RDMA hứa hẹn tăng tốc 2x. Tối ưu hóa cluster phi chính thức (non-RDMA) đang được phát triển, phù hợp cho người sở hữu Mac base model. Tìm hiểu phần mềm mới & kiến thức về phân phối mô hình LLM. #CôngNghệ #AI #Optimize

*(#MAC #AI #Thunderbolt #Clustering Clustering Thunderbolt-4 Macs may incur 10x slowdown, but Thunderbolt-5 RDMA clusters boost speed 2x. Unofficial optimizations for

#MAC #TríTuệNhiệt #Thunderbolt #GộpServer Clustering Mac Mini (Thunderbolt 4) có thể chậm 10x nhưng Thunderbolt 5+RDMA hứa hẹn tăng tốc 2x. Tối ưu hóa cluster phi chính thức (non-RDMA) đang được phát triển, phù hợp cho người sở hữu Mac base model. Tìm hiểu phần mềm mới & kiến thức về phân phối mô hình LLM. #CôngNghệ #AI #Optimize

*(#MAC #AI #Thunderbolt #Clustering Clustering Thunderbolt-4 Macs may incur 10x slowdown, but Thunderbolt-5 RDMA clusters boost speed 2x. Unofficial optimizations for

Data-driven empathy is the future of UX. Moving beyond the limitations of subjective persona creation, we now utilize clustering algorithms to uncover latent user patterns. This methodological shift ensures design decisions are rooted in empirical evidence rather than intuition. This guide at WebHeads United explores the technical frameworks for this synthesis. Refine your audience insights with algorithmic rigour.

https://webheadsunited.com/using-clustering-algorithms-persona-creation/

#DataScience #UXDesign #Clustering #WebDev #Fediverse

"Normalized mutual information is a biased measure for classification and community detection"

#algorithm #classification #clustering #ML #bias #metric

https://www.nature.com/articles/s41467-025-66150-8

GaMAC: Открытая библиотека для автоматической кластеризации мультимодальных данных под GPU

На сегодняшний день не существует полноценного инструментария для кластеризации на графическом процессоре, что стало основным стимулом для создания универсальной библиотеки, способной автоматически решать задачи кластеризации данных различных представлений. Мы представляем GaMAC - библиотека автоматической оптимизации кластеризации с поддержкой с GPU.

https://habr.com/ru/articles/973364/

#кластеризация #clustering #мультимодальность #автоматическое_машинное_обучение #gpu #мультимодальная_кластеризация

GaMAC: Открытая библиотека для автоматической кластеризации мультимодальных данных под GPU

На сегодняшний день не существует полноценного инструментария для кластеризации на графическом процессоре, что стало основным стимулом для создания универсальной библиотеки, способной автоматически решать задачи кластеризации данных различных представлений. Мы представляем GaMAC - библиотека автоматической оптимизации кластеризации с поддержкой с GPU.

https://habr.com/ru/articles/973364/

#кластеризация #clustering #мультимодальность #автоматическое_машинное_обучение #gpu #мультимодальная_кластеризация

GaMAC: Открытая библиотека для автоматической кластеризации мультимодальных данных под GPU

На сегодняшний день не существует полноценного инструментария для кластеризации на графическом процессоре, что стало основным стимулом для создания универсальной библиотеки, способной автоматически решать задачи кластеризации данных различных представлений. Мы представляем GaMAC - библиотека автоматической оптимизации кластеризации с поддержкой с GPU.

https://habr.com/ru/articles/973364/

#кластеризация #clustering #мультимодальность #автоматическое_машинное_обучение #gpu #мультимодальная_кластеризация

GaMAC: Открытая библиотека для автоматической кластеризации мультимодальных данных под GPU

На сегодняшний день не существует полноценного инструментария для кластеризации на графическом процессоре, что стало основным стимулом для создания универсальной библиотеки, способной автоматически решать задачи кластеризации данных различных представлений. Мы представляем GaMAC - библиотека автоматической оптимизации кластеризации с поддержкой с GPU.

https://habr.com/ru/articles/973364/

#кластеризация #clustering #мультимодальность #автоматическое_машинное_обучение #gpu #мультимодальная_кластеризация

When You Need Clustering or SVM Developers for ML Projects

Not sure when your ML project requires expert help? Clustering specialists and SVM developers can make a huge difference when working with complex datasets, uncovering hidden patterns, or building high-accuracy predictive models.

📌 Read the full article on the Amplework blog: https://www.amplework.com/blog/when-you-need-clustering-or-svm-developers/

#MachineLearning #Clustering #SVM #DataScienceExperts #MLProjects #AIEngineering #PredictiveModels #ScalableML #AIDevelopment

Behind the scenes of “beautiful scientific graphics”

If you think that clean, elegant visuals in scientific reports are produced in a couple of clicks — I’m here to disappoint you. 🙂

Here’s one of many failed attempts to visualize results based on thermodynamic modeling of geochemical processes.

Turning raw multidimensional data into something that a human reader can intuitively grasp is a separate challenge — with dozens of input parameters and only a few truly useful outcomes.

Good science is not only about computation, but also about communication.

#Geochemistry #DataViz #Rstats #Clustering #EnvironmentalModelling #ScienceCommunication #PHREEQC #WaterPollution #SvystunovaGully #Contamimation #Groundwater #Infographics #PCA #Thermodynamics

🧠 New preprint by Chintaluri et al. (2025): An ion channel #omnimodel for standardized #biophysical #neuron #modelling. A unified #HodgkinHuxley formalism applied to >3,500 ion channel models from #ModelDB. Enables cross-model comparison, #clustering, and reproducible simulation through a shared parametrization:

🌍 https://doi.org/10.1101/2025.10.03.680368

#CompNeuro #Neuroscience #Reproducibility

🧠 New preprint by Chintaluri et al. (2025): An ion channel #omnimodel for standardized #biophysical #neuron #modelling. A unified #HodgkinHuxley formalism applied to >3,500 ion channel models from #ModelDB. Enables cross-model comparison, #clustering, and reproducible simulation through a shared parametrization:

🌍 https://doi.org/10.1101/2025.10.03.680368

#CompNeuro #Neuroscience #Reproducibility

🧠 New preprint by Chintaluri et al. (2025): An ion channel #omnimodel for standardized #biophysical #neuron #modelling. A unified #HodgkinHuxley formalism applied to >3,500 ion channel models from #ModelDB. Enables cross-model comparison, #clustering, and reproducible simulation through a shared parametrization:

🌍 https://doi.org/10.1101/2025.10.03.680368

#CompNeuro #Neuroscience #Reproducibility

🧠 New preprint by Chintaluri et al. (2025): An ion channel #omnimodel for standardized #biophysical #neuron #modelling. A unified #HodgkinHuxley formalism applied to >3,500 ion channel models from #ModelDB. Enables cross-model comparison, #clustering, and reproducible simulation through a shared parametrization:

🌍 https://doi.org/10.1101/2025.10.03.680368

#CompNeuro #Neuroscience #Reproducibility

🧠 New preprint by Chintaluri et al. (2025): An ion channel #omnimodel for standardized #biophysical #neuron #modelling. A unified #HodgkinHuxley formalism applied to >3,500 ion channel models from #ModelDB. Enables cross-model comparison, #clustering, and reproducible simulation through a shared parametrization:

🌍 https://doi.org/10.1101/2025.10.03.680368

#CompNeuro #Neuroscience #Reproducibility

Wondering what the implications of the structure and attitude of the #Fediverse are for the small world and the spread of cooperation vs antagonism.
#networks #clustering
https://youtu.be/CYlon2tvywA?si=FKjKO1pHoT7DIJ0-

DSM Disorders Disappear in Statistical Clustering of Psychiatric Symptoms

https://www.psychiatrymargins.com/p/traditional-dsm-disorders-dissolve?r=2wyot6&triedRedirect=true

#HackerNews #DSM #Disorders #Statistical #Clustering #Psychiatric #Symptoms #MentalHealth #Research

DSM Disorders Disappear in Statistical Clustering of Psychiatric Symptoms

https://www.psychiatrymargins.com/p/traditional-dsm-disorders-dissolve?r=2wyot6&triedRedirect=true

#HackerNews #DSM #Disorders #Statistical #Clustering #Psychiatric #Symptoms #MentalHealth #Research

DSM Disorders Disappear in Statistical Clustering of Psychiatric Symptoms

https://www.psychiatrymargins.com/p/traditional-dsm-disorders-dissolve?r=2wyot6&triedRedirect=true

#HackerNews #DSM #Disorders #Statistical #Clustering #Psychiatric #Symptoms #MentalHealth #Research

DSM Disorders Disappear in Statistical Clustering of Psychiatric Symptoms

https://www.psychiatrymargins.com/p/traditional-dsm-disorders-dissolve?r=2wyot6&triedRedirect=true

#HackerNews #DSM #Disorders #Statistical #Clustering #Psychiatric #Symptoms #MentalHealth #Research

DSM Disorders Disappear in Statistical Clustering of Psychiatric Symptoms

https://www.psychiatrymargins.com/p/traditional-dsm-disorders-dissolve?r=2wyot6&triedRedirect=true

#HackerNews #DSM #Disorders #Statistical #Clustering #Psychiatric #Symptoms #MentalHealth #Research

🚀 TopicWatchdog – Week 3: Stable Topics with BERTopic

KMeans worked, but cluster IDs kept jumping across retrains. This week I added a Python BERTopic stage with a BigQuery registry → stable topic IDs!

🟢 UMAP + HDBSCAN
🟢 Stable IDs via registry
🟢 Auto-labels with Gemini
🟢 Looker Studio dashboards

📊 3,802 topics → 2,472 mapped, top clusters: migration, economy, climate, politics.

👉 Blog: https://dracoblue.net/dev/topicwatchdog-stable-topics-with-bertopic/

#TopicWatchdog #BERTopic #BigQuery
#Clustering
#MachineLearning
#FediScience

🚀 TopicWatchdog – Week 3: Stable Topics with BERTopic

KMeans worked, but cluster IDs kept jumping across retrains. This week I added a Python BERTopic stage with a BigQuery registry → stable topic IDs!

🟢 UMAP + HDBSCAN
🟢 Stable IDs via registry
🟢 Auto-labels with Gemini
🟢 Looker Studio dashboards

📊 3,802 topics → 2,472 mapped, top clusters: migration, economy, climate, politics.

👉 Blog: https://dracoblue.net/dev/topicwatchdog-stable-topics-with-bertopic/

#TopicWatchdog #BERTopic #BigQuery
#Clustering
#MachineLearning
#FediScience

Summer ☀️ read: a new paper on model-based clustering just appeared in Computo!

Julien Jacques and Brendan Thomas Murphy publish a new method for clustering multivariate count data. The method combines feature selection and clustering, and is based on conditionally independent Poisson mixture models and Poisson generalized linear models.

On simulations, the Adjusted Rand Index (ARI) of the model with selected variables is close to the optimal ARI obtained with the true clustering variables.

The paper and accompanying R code are available at https://computo-journal.org/published-202507-jacques-count-data/

#machineLearning #clustering #Rstats #openScience #openSource #openAccess

Don't pass by the new insightful lecture from Dr. Alejandro Rodriguez Garcia, Abdus Salam International Centre for Theoretical Physics (ICTP)!

In this one, Alex provides a comprehensive overview of various clustering methods, including flat, fuzzy, and hierarchical approaches. His lecture not only discusses the mathematical foundations of techniques like k-means and k-medoids but also highlights their practical applications across fields such as image recognition and data classification.

This lecture is an excellent opportunity to deepen your understanding of unsupervised learning and engage critically with advanced clustering methods.

Join Enabla to watch the lecture and interact with Dr. Rodriguez Garcia for free! Ask questions and spark discussions with both him and the rest of the Enabla community: https://enabla.com/pub/1109/about

#UnsupervisedLearning #MachineLearning #DataScience #Clustering #OpenAccess

Don't pass by the new insightful lecture from Dr. Alejandro Rodriguez Garcia, Abdus Salam International Centre for Theoretical Physics (ICTP)!

In this one, Alex provides a comprehensive overview of various clustering methods, including flat, fuzzy, and hierarchical approaches. His lecture not only discusses the mathematical foundations of techniques like k-means and k-medoids but also highlights their practical applications across fields such as image recognition and data classification.

This lecture is an excellent opportunity to deepen your understanding of unsupervised learning and engage critically with advanced clustering methods.

Join Enabla to watch the lecture and interact with Dr. Rodriguez Garcia for free! Ask questions and spark discussions with both him and the rest of the Enabla community: https://enabla.com/pub/1109/about

#UnsupervisedLearning #MachineLearning #DataScience #Clustering #OpenAccess

Don't pass by the new insightful lecture from Dr. Alejandro Rodriguez Garcia, Abdus Salam International Centre for Theoretical Physics (ICTP)!

In this one, Alex provides a comprehensive overview of various clustering methods, including flat, fuzzy, and hierarchical approaches. His lecture not only discusses the mathematical foundations of techniques like k-means and k-medoids but also highlights their practical applications across fields such as image recognition and data classification.

This lecture is an excellent opportunity to deepen your understanding of unsupervised learning and engage critically with advanced clustering methods.

Join Enabla to watch the lecture and interact with Dr. Rodriguez Garcia for free! Ask questions and spark discussions with both him and the rest of the Enabla community: https://enabla.com/pub/1109/about

#UnsupervisedLearning #MachineLearning #DataScience #Clustering #OpenAccess

Don't pass by the new insightful lecture from Dr. Alejandro Rodriguez Garcia, Abdus Salam International Centre for Theoretical Physics (ICTP)!

In this one, Alex provides a comprehensive overview of various clustering methods, including flat, fuzzy, and hierarchical approaches. His lecture not only discusses the mathematical foundations of techniques like k-means and k-medoids but also highlights their practical applications across fields such as image recognition and data classification.

This lecture is an excellent opportunity to deepen your understanding of unsupervised learning and engage critically with advanced clustering methods.

Join Enabla to watch the lecture and interact with Dr. Rodriguez Garcia for free! Ask questions and spark discussions with both him and the rest of the Enabla community: https://enabla.com/pub/1109/about

#UnsupervisedLearning #MachineLearning #DataScience #Clustering #OpenAccess

Don't pass by the new insightful lecture from Dr. Alejandro Rodriguez Garcia, Abdus Salam International Centre for Theoretical Physics (ICTP)!

In this one, Alex provides a comprehensive overview of various clustering methods, including flat, fuzzy, and hierarchical approaches. His lecture not only discusses the mathematical foundations of techniques like k-means and k-medoids but also highlights their practical applications across fields such as image recognition and data classification.

This lecture is an excellent opportunity to deepen your understanding of unsupervised learning and engage critically with advanced clustering methods.

Join Enabla to watch the lecture and interact with Dr. Rodriguez Garcia for free! Ask questions and spark discussions with both him and the rest of the Enabla community: https://enabla.com/pub/1109/about

#UnsupervisedLearning #MachineLearning #DataScience #Clustering #OpenAccess

Ein lang ersehnter Wunsch von mir: Eigene #Clustering Methoden in #OpenRefine benutzen.

Verfügbar seit Version 3.9.0 und funktioniert seit 3.9.3 auch mit #Jython und #Clojure.

Hier eine Anleitung zur Benutzung im #FDMLab Blog.

https://fdmlab.landesarchiv-bw.de/workshop/openrefine-fortgeschrittene/19-erweitertes-clustering/

#LandesarchivBW