This blog post is about using the Microsoft Academic Graph and NLP to build a personalized recommender system to suggest new scientific publications to researchers maintaining Systematic Literature Reviews.
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 Dat...
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.
A scalable unsupervised approach for driver safety estimation on Pointer Telocation's dataset
We achieved zero-downtime reconfiguration and management of the Spark Streaming job used in Project Fortis with Azure Service Bus.
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 consu...
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 ...
Using GraphQL and Azure to create a data processing pipeline for identifying trends and providing insights about global humanitarian crises.
Storing and querying big data is very challenging, especially when performing real-time queries on huge amounts of data. In this post, I'll share benchmarking results and compare several big data technologies in the context of genomic data queries.
