Discussed the phenomenalprogress over the last decade in the engineering of superconducting devices, the development of high-fidelitygate operations, and quantum non-demolition measurements with high signal to noise ratio.
A quantum engineer’s guide to superconducting qubits Leer más »
«dabl tries to reduce the turnaround time required for a quick baseline estimate of a supervised learning problem. It does so by automating the task of iterating through different techniques of data preprocessing, feature engineering, parameter tuning and model building to generate efficacious baseline models».
Machine Learning with dabl ( 0.1.8) Leer más »
The combined impact of new computing resources and techniques with an increasing avalanche of large datasets, is transforming many research areas and may lead to technological breakthroughs that can be used by billions of people. In the recent years, Machine Learning and especially its subfield Deep Learning have seen impressive advances. Techniques developed within these two fields are now able to analyze and learn from huge amounts of real world examples in a disparate formats. While the number of Machine Learning algorithms is extensive and growing, their implementations through frameworks and libraries is also extensive and growing too.
El objetivo del Programa de Certificación de Ética para Sistemas Autónomos e Inteligentes (ECPAIS) del IEEE SA es crear especificaciones para los procesos de certificación y marcado que promuevan la transparencia, la rendición de cuentas y la reducción del sesgo algorítmico en los Sistemas Autónomos e Inteligentes (A / IS). El objetivo de ECPAIS es
El Programa de Certificación de Ética para Sistemas Autónomos e Inteligentes (ECPAIS) Leer más »