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viernes, 12 de julio de 2019
Every day, healthcare organizations are beginning their digital transformation journey with the Microsoft Healthcare Bot Service built on Azure. The Healthcare Bot service empowers healthcare organizations to build and deploy an Artificial Intelligence (AI) powered, compliant, conversational healthcare experience at scale.
miércoles, 10 de julio de 2019
Through integration with Cognitive Services APIs, Azure Search has long had the ability to extract text and structure from images and unstructured content.
lunes, 8 de julio de 2019
Uno de los integrantes más recientes de la cartera de Azure AI, Form Recognizer, aplica aprendizaje automático avanzado para extraer con precisión texto, pares clave-valor y tablas de los documentos. Con solo algunos ejemplos, adapta su capacidad de reconocimiento a los documentos proporcionados, tanto en el entorno local como en la nube.
miércoles, 3 de julio de 2019
This year at Microsoft Build 2019, we announced a slew of new releases as part of Azure Machine Learning service which focused on MLOps. These capabilities help you automate and manage the end-to-end machine learning lifecycle.
martes, 25 de junio de 2019
The next time you see your physician, consider the times you fill in a paper form. It may seem trivial, but the information could be crucial to making a better diagnosis. Now consider the other forms of healthcare data that permeate your life—and that of your doctor, nurses, and the clinicians working to keep patients thriving.
jueves, 13 de junio de 2019
Customers such as Allscripts, Chevron, J.B. Hunt, and thousands of others are migrating their important workloads to Azure where they find unmatched security. While understanding cloud security is initially a concern to many, after digging in, customers often tell us the security posture they can set up within Azure is easier to implement and far more comprehensive than what they can provide for in other environments.
jueves, 13 de junio de 2019
When data scientists work on building a machine learning model, their experimentation often produces lots of metadata: metrics of models you tested, actual model files, as well as artifacts such as plots or log files. They often try different models and parameters, for example random forests of varying depth, linear models with different regularization rates, or deep learning models with different architectures trained using different learning rates.
jueves, 13 de junio de 2019
Throughout our Internet of Things (IoT) journey we’ve seen solutions evolve from device-centric models, to spatially-aware solutions that provide real-world context.
lunes, 10 de junio de 2019
Data scientists have a dynamic role. They need environments that are fast and flexible while upholding their organization’s security and compliance policies. Notebook Virtual Machine (VM), announced in May 2019, resolves these conflicting requirements while simplifying the overall experience for data scientists.
jueves, 6 de junio de 2019
Build more accurate forecasts with the release of capabilities in automated machine learning. Have scenarios that require have gaps in training data or need to apply contextual data to improve your forecast or need to apply lags to your features? Learn more about the new capabilities that can assist you.
