CSE Developer Blog

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App-to-app communication with React Native on Android

The ixo Foundation is building a decentralized impact evaluation protocol using blockchain and W3C decentralized identifier specification. We worked with them to develop a sample client in React Native, including a native Android plugin for app-to-app communication.

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Sequence Intent Classification Using Hierarchical Attention Networks

We analyze how Hierarchical Attention Neural Networks could be helpful with malware detection and classification scenarios, demonstrating the usefulness of this approach for generic sequence intent analysis. The novelty of our approach is in applying techniques that are used to discover structure in a narrative text to data that describes the behavior of executables.

Azure App Services

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Social Stream Pipeline on Databricks with auto-scaling and CI/CD using Travis

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.

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Orchestrating TURN Servers for Cloud Deployment

We worked with Aveva to build 3DToolkit, a toolkit for creating powerful cloud-based 3D experiences that stream on low-powered devices with WebRTC.

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Permissively-Licensed Named Entity Recognition on the JVM

The ability to correctly identify entities, such as places, people, and organizations, adds a powerful level of natural language understanding to applications. This post introduces a MIT-licensed one-click deployment to Azure for web services that lets developers get started with a wide range of natural language tasks in 5 minutes or less, by consuming simple HTTP services for language identification, tokenization, part-of-speech-tagging and named entity recognition.

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Custom Analytics Dashboard for Application Insights

We created an easy-to-use tool for visualizing data from Microsoft Azure Application Insights with a dashboard framework. Our solution can be applied to different bot scenarios as well as other scenarios involving the service.

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Building an Image Classification Pipeline Using Serverless Architecture

We collaborated on an image classification pipeline to perform automatic face detection and matching using machine learning via Microsoft Cognitive Services Face API. Our project was built with Azure Functions to process images using message queues.

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IoT Sports Sensor Machine Learning Helps Amateurs Up Their Game

We use IoT sensors to collect positional and motion data from professional and amateur skiers to classify expertise and skill level through machine learning.

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Youth Homelessness Survey App with Xamarin.Forms and HockeyApp

We partnered with the Connecticut Coalition to End Homelessness to develop a Xamarin application, WeCount, for volunteers to use to collect survey data for the 2017 Point-In-Time Count.

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Geocoding Social Conversations with NLP and JavaScript

Using Azure Functions and the open-source JavaScript library Compromise for inferring location in social media posts.

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Digital badge building with reusable Web Components

Designing and developing the badge builder for the Duke of York’s iDEA programme with responsive web design, web components and Azure.

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Project Fortis: Accelerating UN Humanitarian Aid Planning with GraphQL

Using GraphQL and Azure to create a data processing pipeline for identifying trends and providing insights about global humanitarian crises.

Big Data

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Assessing The Severity Of Acne Via Cell Phone Selfie Images Using A Deep Learning Model

Nestlé Skin Health partnered with Microsoft to develop a deep learning model powered mobile app able to assess acne severity using only uploaded selfie images as a source.

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Running Parallel Apache Spark Notebook Workloads On Azure Databricks

This article walks through the development of a technique for running Spark jobs in parallel on Azure Databricks. The technique enabled us to reduce the processing times for JetBlue’s reporting threefold while keeping the business logic implementation straight forward. The technique can be re-used for any notebooks-based Spark workload on Azure Databricks.

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Real-time time series analysis at scale for trending topics detection

This code story describes a collaboration with ZenCity around detecting trending topics at scale. We discuss the datasets, data preparation, models used and the deployment story for this scenario.

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Social Stream Pipeline on Databricks with auto-scaling and CI/CD using Travis

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.

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Unsupervised driver safety estimation at scale, a collaboration with Pointer Telocation

A scalable unsupervised approach for driver safety estimation on Pointer Telocation’s dataset

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Runtime Configuration of Spark Streaming Jobs

We achieved zero-downtime reconfiguration and management of the Spark Streaming job used in Project Fortis with Azure Service Bus.

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Azure Event Hub Ingestion at Scale with Python and Kubernetes

We created a solution to ingest Azure Event Hubs events at scale using Python and Kubernetes.

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IoT Sports Sensor Machine Learning Helps Amateurs Up Their Game

We use IoT sensors to collect positional and motion data from professional and amateur skiers to classify expertise and skill level through machine learning.

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Project Fortis: Accelerating UN Humanitarian Aid Planning with GraphQL

Using GraphQL and Azure to create a data processing pipeline for identifying trends and providing insights about global humanitarian crises.

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Reproducible Data Science – Analysis of Experimental Data with Pachyderm and Azure

We partnered with General Fusion to develop and deploy their new Pachyderm-based data infrastructure to Microsoft Azure. This post walks through General Fusion’s new data architecture and how we deployed it to Azure.

Blockchain

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Using Blockchain To Securely Transfer And Verify Files

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.

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Using uPort For Authentication On Blockchain To Improve Standards On The Food Logistics Chain

Food ingredients travel thousands of miles along logistics chains. One bad batch of produce can ruin a restaurant’s reputation, but it’s hard to identify who’s at fault. CSE has worked with Hitachi to build a sample infrastructure leveraging blockchain – thus achieving a new level of accountability for those producing, storing and serving food.

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Building a Private Ethereum Consortium

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 to peer across virtual networks.

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App-to-app communication with React Native on Android

The ixo Foundation is building a decentralized impact evaluation protocol using blockchain and W3C decentralized identifier specification. We worked with them to develop a sample client in React Native, including a native Android plugin for app-to-app communication.

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Using a Private Ethereum Consortium Network to Store and Validate Documents

We developed a blockchain-based solution for storing, tracking, providing and validating pesticide level measurements.

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Using Helm to Deploy Blockchain to Kubernetes

We recently worked with Webjet to migrate their deployment from IaaS to Kubernetes and used Helm to deploy a private Ethereum network to Kubernetes.

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Using a Layer 7 Proxy for Ethereum Blockchain Client’s JSON-RPC Endpoint

This walk-through shows how to use a Layer 7 proxy on Azure to protect an Ethereum Blockchain client’s JSON-RPC endpoint and provide additional capabilities, such as secure channels, tracking, and even analytics.

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Stampery Blockchain Add-in for Microsoft Office

Creating an add-in for Microsoft Office to certify and verify documents using the Stampery APIs and blockchain technology.

Bots

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Analysing Bot to Human Hand-off Interactions

A common use case in the bot-verse is the ability to hand over a customer conversation from a bot to a human, and the vital need for a feedback loop for this kind of scenario. From this, we developed a Hand-off Dashboard Template that can be used within the Ibex dashboard to provide users with important information about how their bot and agents are working with customers.

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Creating a Data Visualization GraphQL Server with a Loosely Coupled Schema

We share how we built a flexible data visualization dashboard by leveraging the GraphQL stack.

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Custom Analytics Dashboard for Application Insights

We created an easy-to-use tool for visualizing data from Microsoft Azure Application Insights with a dashboard framework. Our solution can be applied to different bot scenarios as well as other scenarios involving the service.

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Using Microsoft Bot Framework as a Proxy to Publish your Bot Stack

With our solution, users can publish bot dialogs from any backend directly to MIcrosoft Bot Framework channels, with custom Navigator logic if needed.

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Developing a Custom Search Engine for an Expert Chat System

We address the challenge of creating a custom search experience for a specific domain area. We also provide a guide for creating your own custom search experience by leveraging Azure Search and Cognitive Services and sharing custom code for iterative testing, measurement and indexer redeployment.

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Facilitating Growth Capital Funding in Africa with Bots

We built a bot with Microsoft Bot Framework (MBF) to tap into a multitude of channels, including a client’s existing Android app, and implemented localization features, to connect with potential customers on their preferred online platforms.

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Bot to Human Handoff in Node.js

When considering bots, it’s often important for organizations to have the ability to “hand off” a customer from a bot to a human agent seamlessly. We implemented an unopinionated e-2-e solution called Handoff for bot authors to implement a variety of scenarios, using the Microsoft Bot Framework Node.js SDK.

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Deploying bots using the Serverless framework

Microsoft partnered with MaaS Global to build a bot using the Microsoft Bot Framework Node.js SDK that can be deployed with the Serverless framework.

Collecting Form Data with a LUIS-Based Bot

This post outlines the steps of creating a bot that interacts with a user to collect missing LUIS entity data before processing their request.

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Orchestrating Multiple Bots with Multilingual Support

Using Microsoft Bot Framework, we were able to create an easy to maintain “Orchestration Bot” that can both manage sub-bots and provide multilingual support.

Cognitive Services

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Social Stream Pipeline on Databricks with auto-scaling and CI/CD using Travis

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.

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Semantic Segmentation of Small Data using Keras on an Azure Deep Learning Virtual Machine

Golf performance tracking startup Arccos joined forces with Commercial Software Engineering (CSE) developers in hopes of unveiling new improvements to their “virtual caddie” this summer.

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Making sense of Handwritten Sections in Scanned Documents using the Azure ML Package for Computer Vision and Azure Cognitive Services

Extracting general concepts, rather than specific phrases, from documents and contracts is challenging. It’s even more complicated when applied to scanned documents containing handwritten annotations. We describe using object detection and OCR with Azure ML Package for Computer Vision and Cognitive Services API.

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Giving meaningful context to social media influence with Microsoft Cognitive Services

When it comes to identifying and understanding influential voices in social media, context is key. See how we used topic detection, sentiment analysis, and Azure Functions to automate context-aware social media insights.

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Comparing Image-Classification Systems: Custom Vision Service vs. Inception

This story covers how to get started with transfer-learning and build image classification models in Python with the Custom Vision Service. We compare the results with the popular Tensorflow-based models Inception and MobileNet.

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Building a Custom Spark Connector for Near Real-Time Speech-to-Text Transcription

This post describes in detail the Azure Cognitive Services speech-to-text WebSocket protocol and shows how to implement the protocol in Java. This enables us to transcribe audio to text in near real-time. We then show how to feed the transcribed radio into a pipeline based on Spark Streaming for further analysis, augmentation, and aggregation. The Java client is reusable across a wide range of text-to-speech scenarios that require time-efficient speech-to-text transcription in more than 10 languages including English, French, Spanish, German and Chinese.

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Using Microsoft Bot Framework as a Proxy to Publish your Bot Stack

With our solution, users can publish bot dialogs from any backend directly to MIcrosoft Bot Framework channels, with custom Navigator logic if needed.

Image searchlifecycle
Developing a Custom Search Engine for an Expert Chat System

We address the challenge of creating a custom search experience for a specific domain area. We also provide a guide for creating your own custom search experience by leveraging Azure Search and Cognitive Services and sharing custom code for iterative testing, measurement and indexer redeployment.

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Automating Receipt Processing

Claiming expenses is usually a manual process. This project aims to improve the efficiency of receipt processing by looking into ways to automate this process.  << You need to include a little more context here.  I understand that you don’t want to name the partner,

Containers

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Preventing Rhino Poaching With Microsoft Azure

Peace Parks Foundation partnered with Microsoft to build a scalable alerting system that helps to fight rhino poaching in South Africa.

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Developing and Deploying a Churn Prediction Model with Azure Machine Learning Services

Deep learning algorithms capable of learning and predicting customer behavior are allowing businesses to intervene with the right retention offers at the right time. CSE recently partnered with Majid Al Futtaim Ventures (MAF) to design and deploy a machine learning solution to predict attrition.

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How to Build A K8S Http API For Helm, and Serve Micro-services Using A Single IP

The Commercial Software Engineering team (CSE) partnered with Axonize to automate the process of deploying apps to Kubernetes, and expose these apps to the internet via a single IP.

This post is about enabling applications in your Kubernetes cluster to programmatically install helm charts and expose them through a single public facing IP.

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Infrastructure as Code – On demand GPU clusters with Terraform & Jenkins

Developing robust algorithms for self-driving cars requires sourcing event data from over 10 billion hours of recorded driving time. CSE worked with Cognata, a startup developing simulation platforms for autonomous vehicles, to build a Jenkins pipeline and Terraform solution that enabled our partner to dynamically scale GPU resources for their simulations.

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Deploying a Batch AI Cluster for Distributed Deep Learning Model Training

Microsoft and Land O’Lakes partnered to develop an automated solution to identify sustainable farming practices given thousands of satellite images of Iowan farms. Our primary goal was to reduce the reliance on manual interviewing of farmers and make it more profitable for farmers to follow sustainable farming practices. To tackle this issue our team deployed a highly scalable Batch AI cluster on Azure and then performed distributed deep learning model training with Horovod.

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Building a Private Ethereum Consortium

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 to peer across virtual networks.

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Packaging an Electron app for managed distribution across devices

We developed an Electron-based app using Microsoft Intune cloud service for management and distribution across a broad range of devices.

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Using Helm to Deploy Blockchain to Kubernetes

We recently worked with Webjet to migrate their deployment from IaaS to Kubernetes and used Helm to deploy a private Ethereum network to Kubernetes.

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Orchestrating TURN Servers for Cloud Deployment

We worked with Aveva to build 3DToolkit, a toolkit for creating powerful cloud-based 3D experiences that stream on low-powered devices with WebRTC.

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Azure Event Hub Ingestion at Scale with Python and Kubernetes

We created a solution to ingest Azure Event Hubs events at scale using Python and Kubernetes.

CSE

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Attaching and Detaching an Edge Node From a HDInsight Spark Cluster when running Dataiku Data Science Studio (DSS)

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.  

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OAuth 2.0 for Mixed Reality applications

We worked with Aveva to build 3DToolkit, a toolkit for creating cloud-based 3D experiences that securely stream to low-powered devices using WebRTC.

DevOps

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Developing and Deploying a Churn Prediction Model with Azure Machine Learning Services

Deep learning algorithms capable of learning and predicting customer behavior are allowing businesses to intervene with the right retention offers at the right time. CSE recently partnered with Majid Al Futtaim Ventures (MAF) to design and deploy a machine learning solution to predict attrition.

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Social Stream Pipeline on Databricks with auto-scaling and CI/CD using Travis

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.

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Infrastructure as Code – On demand GPU clusters with Terraform & Jenkins

Developing robust algorithms for self-driving cars requires sourcing event data from over 10 billion hours of recorded driving time. CSE worked with Cognata, a startup developing simulation platforms for autonomous vehicles, to build a Jenkins pipeline and Terraform solution that enabled our partner to dynamically scale GPU resources for their simulations.

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Packaging an Electron app for managed distribution across devices

We developed an Electron-based app using Microsoft Intune cloud service for management and distribution across a broad range of devices.

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Copy Custom VM Images on Azure

We created an azure-cli extension to simplify the process of distributing VM images globally.

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Orchestrating TURN Servers for Cloud Deployment

We worked with Aveva to build 3DToolkit, a toolkit for creating powerful cloud-based 3D experiences that stream on low-powered devices with WebRTC.

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Continuous Delivery for Service Fabric via Github, Travis CI and Docker Compose

This article describes how to use GitHub, Travis CI and Docker Compose to build a simple continuous delivery pipeline to deploy Linux Docker containers to a Service Fabric cluster of Linux hosts.

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Deploying a Linux Python web application to Service Fabric via Docker Compose

This article covers how to take a standard Python web service consisting of an application tier, a WSGI server, and a Nginx reverse proxy and deploy it via Linux containers to a Linux cluster managed by Azure Service Fabric using only simple tooling like Docker Compose.

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Bird Detection with Azure ML Workbench

We demonstrate how to train Object Detection models using CNTK and Tensoflow DNN frameworks. Azure ML Workbench is used as the main training and model hosting infrastructure.

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Moving High Scale Data and Compute from AWS to Azure for The Emedgene Genetics Intelligence Platform

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.

Frameworks

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Real-time Streaming Of 3D Enterprise Applications From The Cloud To Low-powered Devices

Microsoft recently partnered with AVEVA, an engineering, design and management software provider to the Power, Oil & Gas and Marine industries. AVEVA’s challenge is one that is becoming more and more common in the construction visualization space: ever increasing complexity of 3D data that needs to be highly interactive to a customer base that operates on mobile platforms (smartphones,

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Packaging an Electron app for managed distribution across devices

We developed an Electron-based app using Microsoft Intune cloud service for management and distribution across a broad range of devices.

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App-to-app communication with React Native on Android

The ixo Foundation is building a decentralized impact evaluation protocol using blockchain and W3C decentralized identifier specification. We worked with them to develop a sample client in React Native, including a native Android plugin for app-to-app communication.

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Voronoi Selection for Cancer Drug Network Visualization in Mixed Reality

We developed a Voronoi selection feature to improve the node selection experience in a HoloLens app that enables physicians to visualize cancer drug networks in 3D.

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Creating a Data Visualization GraphQL Server with a Loosely Coupled Schema

We share how we built a flexible data visualization dashboard by leveraging the GraphQL stack.

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Youth Homelessness Survey App with Xamarin.Forms and HockeyApp

We partnered with the Connecticut Coalition to End Homelessness to develop a Xamarin application, WeCount, for volunteers to use to collect survey data for the 2017 Point-In-Time Count.

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Revisiting InterOp with Unity, UWP and DirectX

As Unity applications become more complex, the need arises to extend Unity to provide additional capabilities. In our work with Aveva, we used Unity’s plugin architecture to utilize the workstation and server GPU, while still leveraging the Unity runtime for input and display.

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Hacking React Native Unbundles into UWP

We recently worked on developing “unbundle” support for react-native-windows to reduce launch times and memory usage for React Native Windows apps.

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Building Facebook.Yoga for UWP and WPF

We recently worked to bring greater parity to react-native-windows by building cross-platform layout library Facebook.Yoga for UWP and WPF as the React Native framework for iOS and Android switched to use Yoga.

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Project Fortis: Accelerating UN Humanitarian Aid Planning with GraphQL

Using GraphQL and Azure to create a data processing pipeline for identifying trends and providing insights about global humanitarian crises.

Internet Of Things

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How to Build A K8S Http API For Helm, and Serve Micro-services Using A Single IP

The Commercial Software Engineering team (CSE) partnered with Axonize to automate the process of deploying apps to Kubernetes, and expose these apps to the internet via a single IP.

This post is about enabling applications in your Kubernetes cluster to programmatically install helm charts and expose them through a single public facing IP.

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Azure Event Hub Ingestion at Scale with Python and Kubernetes

We created a solution to ingest Azure Event Hubs events at scale using Python and Kubernetes.

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IoT Sports Sensor Machine Learning Helps Amateurs Up Their Game

We use IoT sensors to collect positional and motion data from professional and amateur skiers to classify expertise and skill level through machine learning.

Machine Learning

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Preventing Rhino Poaching With Microsoft Azure

Peace Parks Foundation partnered with Microsoft to build a scalable alerting system that helps to fight rhino poaching in South Africa.

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Assessing The Severity Of Acne Via Cell Phone Selfie Images Using A Deep Learning Model

Nestlé Skin Health partnered with Microsoft to develop a deep learning model powered mobile app able to assess acne severity using only uploaded selfie images as a source.

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Developing and Deploying a Churn Prediction Model with Azure Machine Learning Services

Deep learning algorithms capable of learning and predicting customer behavior are allowing businesses to intervene with the right retention offers at the right time. CSE recently partnered with Majid Al Futtaim Ventures (MAF) to design and deploy a machine learning solution to predict attrition.

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Real-time time series analysis at scale for trending topics detection

This code story describes a collaboration with ZenCity around detecting trending topics at scale. We discuss the datasets, data preparation, models used and the deployment story for this scenario.

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Improving Safety and Efficiency in BMW Manufacturing Plants with an Open Source Platform for Managing Inventory Delivery

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.

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Active Learning for Object Detection in Partnership with Conservation Metrics

CSE teamed up with Conservation Metrics to use Active Learning to allow for more efficient data labeling for object detection projects.

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Unsupervised driver safety estimation at scale, a collaboration with Pointer Telocation

A scalable unsupervised approach for driver safety estimation on Pointer Telocation’s dataset

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Semantic Segmentation of Small Data using Keras on an Azure Deep Learning Virtual Machine

Golf performance tracking startup Arccos joined forces with Commercial Software Engineering (CSE) developers in hopes of unveiling new improvements to their “virtual caddie” this summer.

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Deploying a Batch AI Cluster for Distributed Deep Learning Model Training

Microsoft and Land O’Lakes partnered to develop an automated solution to identify sustainable farming practices given thousands of satellite images of Iowan farms. Our primary goal was to reduce the reliance on manual interviewing of farmers and make it more profitable for farmers to follow sustainable farming practices. To tackle this issue our team deployed a highly scalable Batch AI cluster on Azure and then performed distributed deep learning model training with Horovod.

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Satellite Images Segmentation and Sustainable Farming

Can Machine Learning help with detecting sustainable farming practices? In this blog post inspired by our collaboration with Land O’Lakes we share the lessons we learned in the image segmentation space.