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    CSE Developer Blog

    Big Data - CSE Developer Blog

    Observability for Event Stream Processing with Azure Functions, Event Hubs, and Application Insights
    Observability for Event Stream Processing with Azure Functions, Event Hubs, and Application Insights
    May 13, 2021 May 13, 2021 05/13/21
    Shervyna Ruan
    With distributed tracing handled by Azure Functions, Azure Event Hubs, and Azure Application Insights behind the scenes, Azure Application Insights provides useful monitoring visualizations of the system that helped us easily understand system performances and troubleshoot failures.

    Comments are closed.0CSEAzure App ServicesBig Data
    Assessing the Severity of Acne via Cell Phone Selfie Images Using A Deep Learning Model
    Assessing the Severity of Acne via Cell Phone Selfie Images Using A Deep Learning Model
    February 5, 2019 Feb 5, 2019 02/5/19
    Hang Zhang
    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.

    Comments are closed.0Big DataMachine Learning
    Running Parallel Apache Spark Notebook Workloads On Azure Databricks
    Running Parallel Apache Spark Notebook Workloads On Azure Databricks
    January 18, 2019 Jan 18, 2019 01/18/19
    Clemens Wolff
    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.

    Comments are closed.0Big Data
    Real-Time Time Series Analysis at Scale for Trending Topics Detection
    Real-Time Time Series Analysis at Scale for Trending Topics Detection
    January 2, 2019 Jan 2, 2019 01/2/19
    Omri Mendels
    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.

    Comments are closed.0Big DataMachine Learning
    Social Stream Pipeline on Databricks with auto-scaling and CI/CD using Travis
    Social Stream Pipeline on Databricks with auto-scaling and CI/CD using Travis
    December 12, 2018 Dec 12, 2018 12/12/18
    Mor Shemesh
    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.

    Comments are closed.0Azure App ServicesBig DataCognitive Services
    Unsupervised driver safety estimation at scale, a collaboration with Pointer Telocation
    Unsupervised driver safety estimation at scale, a collaboration with Pointer Telocation
    July 30, 2018 Jul 30, 2018 07/30/18
    Omri Mendels
    A scalable unsupervised approach for driver safety estimation on Pointer Telocation's dataset

    Comments are closed.0Big DataMachine Learning
    Runtime Configuration of Spark Streaming Jobs
    Runtime Configuration of Spark Streaming Jobs
    May 1, 2018 May 1, 2018 05/1/18
    Kevin Hartman
    We achieved zero-downtime reconfiguration and management of the Spark Streaming job used in Project Fortis with Azure Service Bus.

    Comments are closed.0Big Data
    Azure Event Hub Ingestion at Scale with Python and Kubernetes
    Azure Event Hub Ingestion at Scale with Python and Kubernetes
    January 24, 2018 Jan 24, 2018 01/24/18
    Tomer Rosenthal
    We created a solution to ingest Azure Event Hubs events at scale using Python and Kubernetes.

    Comments are closed.0Big DataContainersInternet Of Things
    IoT Sports Sensor Machine Learning Helps Amateurs Up Their Game
    IoT Sports Sensor Machine Learning Helps Amateurs Up Their Game
    June 29, 2017 Jun 29, 2017 06/29/17
    Patty Ryan
    We use IoT sensors to collect positional and motion data from professional and amateur skiers to classify expertise and skill level through machine learning.

    Comments are closed.0Azure App ServicesBig DataInternet Of Things
    Project Fortis: Accelerating UN Humanitarian Aid Planning with GraphQL
    Project Fortis: Accelerating UN Humanitarian Aid Planning with GraphQL
    May 10, 2017 May 10, 2017 05/10/17
    Erik Schlegel
    Using GraphQL and Azure to create a data processing pipeline for identifying trends and providing insights about global humanitarian crises.

    Comments are closed.0Azure App ServicesBig DataFrameworks
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