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EOS DATA ANALYTICS
Feature market insights and perspectives from top C-Level executives, elite technology influencers and thought leaders from your company here. This signature initiative has garnered immense support...
https://www.satellitetoday.com | October 08, 2019
EOS Data Analytics (EOS), a space portfolio company of Noosphere Ventures, unveiled EOS SAR a project to develop its own Synthetic Aperture Radar (SAR) sensors intended for deployment in a constellation of microsatellites.EOS has more than five years of experience in developing data analytics products and cloud services for optical and SAR data from satellites. EOS engineers have already designed a radar prototype and are moving ahead with the development of a SAR payload for small satellites wi...
techhq.com | January 13, 2020
Transporting one million commuters each day, 92 percent of Dutch Railways Nederlandse Spoorwegen’s (NS) trains arrive on time, making it the third-most punctual rail service in the world, behind Switzerland and Japan. While certain delays are unavoidable results of severe weather or obstructions on the line, for exampleNS owes its industry-leading scheduling to big data analytics, thanks to thousands of sensors on its locomotives. As reported in TNW, NS has been leveraging the power of pre...
healthcareitnews.com | January 13, 2020
Healthcare providers are failing to integrate digital data platforms into their IT infrastructure, and and analytics into their clinical and operational workflows. This despite widespread availability of the technology and a definite need for it, given the demands of value-based reimbursement.Those were among the findings of a Black Book survey of 748 providers organizations, which found utilization of advanced analytics was described as "negligible" by a whopping 80% of respondents.Me...
https://analyticsindiamag.com | January 14, 2020
AutoML or automated machine learning has witnessed an exponential rise when it comes to being adopted by the organisations. AutoML can be said as the next wave of machine learning which helps to bridge the gap between talent landscape and complex workflows. Previously in one of our articles, we had discussed the functionality of AutoML and how it solves data science problems. Building complex deep learning models from scratch can be said as one of the most time-consuming and challenging tasks in...
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