Belfast SQL Server User Group

Welcome to the Belfast Chapter

Next Meeting

Thursday,

October

25

Raspberry Pi to Power BI and R to Azure Machine Learning

  • In-Person @ 18 Ormeau Avenue Belfast, Antrim, United Kingdom (map)
  • 18:00 - 20:30 GMT Daylight Time
  • Language: English

Approx. Running order for the night

  • 6:00 - 6:15: Registration & Intro
  • 6:15 - 7:15: Raspberry Pi to Power BI.
  • 7:15 - 7:30: Break and Refreshments
  • 7:30 - 8:30: R to Azure Machine Learning.

Sign Up https://www.eventbrite.co.uk/e/raspberry-pi-to-power-bi-and-r-to-azure-machine-learning-tickets-50638800014

Featured Presentation:

From Raspberry Pi to Power BI and lots in between

Ben Watt, BI Consultant

In this session Ben will walk you through a home-made IoT project with the data ultimately landing in Power BI for visualisation. A Raspberry Pi is the IoT device, with sensors and camera attached to give an end-to-end streaming solution. You will see Python used to run the program and process the images. Microsoft Azure plays its part where Microsoft Cognitive Services enriches the images with facial attributes and recognition, Azure SQL stores the metadata, Azure Blob storage holds the images, Power BI visualises the activity and Microsoft Flow sends mobile notifications. You'll see enough to walk out and get your own project started straight away!

About Ben:
Ben Watt is a Dublin-based BI consultant specialising in Power BI and SQL Server, with interests across the growing Azure data platform stack covering Cognitive Services, Flow, Event Hubs, Power Apps more

Microsoft’s Cloud Machine Learning Service: From R to Azure Machine Learning(AML)

Yongyang Huo, Data Scientist

Similar as Amazon, Google and IBM, Microsoft also released the Clouding Machine Learning Service – the Azure Machine Learning studio, which gives you an interactive, visual workspace to easily build, test, and iterate on a predictive analysis model. In this session, we will walk through some simple machine learning examples that were built in Azure Machine Learning Studio. The learning procedure includes data collection, data cleansing, feature engineering, data mining and model deployed (web services). There is barely any programming required in these AML examples, most of the time just visually connecting datasets and modules to construct the predictive analysis model. However, since AML supports R and Python, some R codes are included for more choice of modelling algorithms and visualization.

About Yongyang:
Yongyang Huo is a Data Scientist specialised in Data Mining, Algorithm Design, Data Modeling and Business Intelligence. His modified algorithm ‘semi-supervised clustering’ has been applied to open source data mining tool forum in 2008.

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