mercredi 3 juillet 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.
lundi 24 juin 2019
With the proliferation of patient information from established and current sources, accompanied with scrupulous regulations, healthcare systems today are gradually shifting towards near real-time data integration.
lundi 10 juin 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.
mardi 4 juin 2019
The automated machine learning capability in Azure Machine Learning service allows data scientists, analysts, and developers to build machine learning models with high scalability, efficiency, and productivity all while sustaining model quality.
mardi 14 mai 2019
In Craig Kerstiens‘s latest blog post, “A health check playbook for your Postgres database” he emphasizes the need for periodic checks for your Postgres databases to ensure it’s healthy and performing well.
jeudi 9 mai 2019
At Microsoft Build 2019 we announced MLOps capabilities in Azure Machine Learning service. MLOps, also known as DevOps for machine learning, is the practice of collaboration and communication between data scientists and DevOps professionals to help manage the production of the machine learning (ML) lifecycle.
lundi 6 mai 2019
Le bouleversement numérique a créé un potentiel illimité pour permettre aux entreprises d’utiliser des données comme un avantage concurrentiel pour leur activité. Par conséquent, l’analytique reste une priorité absolue pour les entreprises. En termes d’analytique, les clients nous disent avoir besoin d’une solution qui offre des performances, une sécurité et une confidentialité optimales au meilleur prix, ainsi qu’un système capable de fournir facilement des insights pertinents dans toute l’organisation. Ils peuvent compter sur Azure.
mercredi 1 mai 2019
Recommendation systems are used in a variety of industries, from retail to news and media. If you’ve ever used a streaming service or ecommerce site that has surfaced recommendations for you based on what you’ve previously watched or purchased, you’ve interacted with a recommendation system.
lundi 29 avril 2019
The Jupyter Notebook on HDInsight Spark clusters is useful when you need to quickly explore data sets, perform trend analysis, or try different machine learning models. Not being able to track the status of Spark jobs and intermediate data can make it difficult for data scientists to monitor and optimize what they are doing inside the Jupyter Notebook.
mardi 9 avril 2019
DevOps is the union of people, processes, and products to enable the continuous delivery of value to end users. DevOps for machine learning is about bringing the lifecycle management of DevOps to Machine Learning.