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Articles récents
- Clustering Time Series with PCA and DBSCAN
- Deploy Enterprise-Ready AI with Dell PowerEdge and Intel® Gaudi® 3
- Roofline AI’s Role in Advancing Compiler Technology with oneAPI
- UT Austin’s HackTX 2024 Hackathon: Top Projects Built Using Intel® AI Technologies
- Transforming 2D Designs into Stunning 3D Creations Using AI with Adobe Creative Cloud and Substance
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Neural networks news
Intel NN News
- Clustering Time Series with PCA and DBSCAN
This article shows how to perform clustering of time series data using PCA and DBSCAN.
- Deploy Enterprise-Ready AI with Dell PowerEdge and Intel® Gaudi® 3
Learn about the newly launched Dell Generative AI Solutions with Intel, powered by Dell PowerEdge […]
- Roofline AI's Role in Advancing Compiler Technology with oneAPI
Intel® Liftoff member, Roofline AI took the stage at the oneAPI DevSummit to showcase its […]
- Clustering Time Series with PCA and DBSCAN
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Archives mensuelles : juillet 2023
Are all Transformer Layers Necessary? Novel Adaptive Inference Method Presented at ACL 2023
Intel Labs and the Hebrew University of Jerusalem present SWEET, an adaptive Inference method for text classification at this year’s ACL conference.
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Chronic Kidney Disease Risk Prediction using Modin and scikit-learn* (sklearn): Developer Spotlight
Developer Spotlight: Arnab Das proposed a solution to Chronic Kidney Disease Risk Prediction
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IT Requirements for Effective AI Planning
According to a whitepaper from ABi Research, every AI investment must be a forward-looking business decision. As the 2020s are shaping up as the decade of Artificial Intelligence, businesses have increased their AI budgets significantly.
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Enterprise AI: Growing Momentum, But Who is Driving?
According to a survey and white paper from Omdia Consulting, the focus is shifting towards the developer’s role in creating, implementing, and maintaining diverse AI models that can be efficiently developed and trained, and that are compatible with various software … Continuer la lecture
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Modin Reaches 10M Downloads
Modin, the open-source scalable drop-in replacement for pandas, has reached 10M downloads.
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