Microsoft Weekly Data Science News for August 24, 2018

The latest articles from Microsoft regarding cloud data science products and updates.

  • Build Intelligent Web App with Machine Learning ServiceIn an earlier article: How to operationalize TensorFlow models in Microsoft Machine Learning Server, we showed how you can deploy a TensorFlow image classification model pre-trained using ImageNet as service in Machine Learning Server, and download a …[Read More]
  • Measuring Model Goodness – Part 1Data and AI are transforming businesses worldwide from finance … actionable insights. This is where data science and machine learning come in. This entire process has been documented as the Team Data Science Process (TDSP) at Microsoft, captured in …[Read More]
  • Driving industry transformation with Azure – Getting started – Edition 1Banking customers want more from their services … using AI and machine learning to detect patient risk and identify disease faster while maintaining privacy and protecting against fraud. IoT in manufacturing isn’t just about collecting data.[Read More]
  • Speech Services August 2018 updateWe are pleased to announce the release of another update to the Cognitive Services Speech SDK (version 0.6.0 … dev kits to significantly improve the audio quality of the audio data collected via the dev kits’ microphones, for high speech recognition …[Read More]
  • Introducing yet another approach for iot compiler toolchains – iotziotz is an extension based containerized wrapper for other IoT compiler toolchains. There are many toolchains with specific needs and way of using. We developed this experimental tool to make compiling things easier. – cross compiling tools are mostly …[Read More]
  • Design against crime & Microsoft Azure with ShinyIt is this app we will later learn how to deploy a shiny app onto Microsoft Azure services … including a review of data available via police.uk. We engaged with UCL to find a student from the Security and Crime Science course who could help us to …[Read More]
  • Simplifying big data analytics architecturemanufacturing, retail education, nonprofit, government, healthcare, media, banking, telecommunication, insurance, and many more industries ranging in use cases from ETL to Data Warehousing, from Machine Learning to IoT, and more.[Read More]
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