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Adding Explainability to Clustering

Analytics Vidhya

Explainable AI is no longer just an optional add-on when using ML algorithms for corporate decision making. The post Adding Explainability to Clustering appeared first on Analytics Vidhya. Introduction The ability to explain decisions is increasingly becoming important across businesses.

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Fluidstack to Deploy Exascale GPU Clusters in Europe with NVIDIA, Borealis Data Center and Dell

insideBIGDATA

Fluidstack, an AI cloud platform, announced it is deploying and managing exascale clusters across Iceland and Europe in collaboration with Borealis Data Center, Dell Technologies and NVIDIA. Our mission has.

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Research: A periodic table for machine learning

Dataconomy

The idea is deceptively simple: represent most machine learning algorithmsclassification, regression, clustering, and even large language modelsas special cases of one general principle: learning the relationships between data points. Each guest (data point) finds a seat (cluster) ideally near friends (similar data).

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#47 Building a NotebookLM Clone, Time Series Clustering, Instruction Tuning, and More!

Towards AI

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! We’re also excited to share updates on Building LLMs for Production, now available on our own platform: Towards AI Academy. Louis-François Bouchard, Towards AI Co-founder & Head of Community 🎉 Great news!

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Announcing Ray support on Databricks and Apache Spark Clusters

databricks

Ray is a prominent compute framework for running scalable AI and Python workloads, offering a variety of distributed machine learning tools, large-scale hyperparameter.

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YC closes deal with Google for dedicated compute cluster for AI startups

Hacker News

Google Cloud is giving Y Combinator startups access to a dedicated, subsidized cluster of Nvidia graphics processing units and Google tensor processing

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Identification of Hazardous Areas for Priority Landmine Clearance: AI for Humanitarian Mine Action

ML @ CMU

In close collaboration with the UN and local NGOs, we co-develop an interpretable predictive tool for landmine contamination to identify hazardous clusters under geographic and budget constraints, experimentally reducing false alarms and clearance time by half. The major components of RELand are illustrated in Fig.