MOOG came to CSE in hopes of building a technology solution that would prove the provenance and transfer of digital assets securely between parties. Working together, Microsoft and MOOG set out to develop a demo of this solution that leverages Azure and blockchain technology.
In the last eight years, poaching in Africa has been happening at an alarming rate. Currently, the continent loses three rhinos a day. As part of our team’s mission to find new ways that technology can positively impact our world, we’ve been collaborating with the Combating Wildlife Crime team Peace Parks Foundation (PPF), in partnership with
Over the course of twelve months Microsoft and BMW partnered three different times to help BMW with its vision for technical transformation. An open-source package called ROS-Industrial was used to help provide the building blocks for the robotics work.
This code story describes CSE's work with ZenCity to create a data pipeline on Azure Databricks supported by a CI/CD pipeline on TravisCI. The aim of the collaboration was to create a pipeline capable of processing a stream of social posts, analyzing them, and identifying trends.
Earlier this year, Dataiku and Microsoft joined forces to add extra flexibility to DSS on HDInsight, and also to allow Dataiku customers to attach a persistent edge node on an HDInsight cluster – something which was previously not a feature supported by the most recent edition of Azure HDInsight. Â
A scalable unsupervised approach for driver safety estimation on Pointer Telocation's dataset
Over the past two years, Microsoft and Webjet have collaborated to build a blockchain-based solution, Rezchain, to help travel companies reduce payment disputes. In this code story, we’ll share the lessons learned in creating the Rezchain consortium. In particular, we'll focus on how we solved the challenges involved with enabling Ethereum nodes t...
We created an azure-cli extension to simplify the process of distributing VM images globally.
We explore how we worked with a customer to add autoscaling capability to a Kubernetes cluster to meet bursty demands for deep learning training in a cost-efficient manner.
We demonstrate how we migrated the compute resources of a genomics intelligence platform to Azure, transferring more than 100 TB of blob storage and handling application secrets without embedding the Azure SDK.
