Remove 2018 Remove Algorithm Remove Data Silos
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Data Integrity: The Foundation for Trustworthy AI/ML Outcomes and Confident Business Decisions

ODSC - Open Data Science

As critical data flows across an organization from various business applications, data silos become a big issue. The data silos, missing data, and errors make data management tedious and time-consuming, and they’re barriers to ensuring the accuracy and consistency of your data before it is usable by AI/ML.

ML 98
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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 2

AWS Machine Learning Blog

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

AWS 101
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Meet the winners of Phase 1 of the PREPARE Challenge

DrivenData Labs

Find, curate, or contribute data to create representative and open datasets that can be used for early prediction of AD/ADRD. Advance algorithms and analytic approaches for early prediction of AD/ADRD, with an emphasis on explainability of predictions. Dr. Reid also teaches Data Science at the University of California at Berkeley.

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Core4ce Cyberscape: the cyber security forensics platform

Cambridge Intelligence

Core4ce Cyberscape: unmasking cyber threats Since 2018, Core4ce’s team of data scientists, engineers, and cyber experts has helped the US federal government solve complex challenges with data. Bridging data silos Once we have our seed nodes on the chart, we start enriching them.