Machine Learning without a PhD in Statistics! Microsoft Azure ML DeepDive

This is a past event

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Machine learning is the science of making computers act without being unambiguously programmed - something we use every day when we search and shop on the web and talk to our devices. Microsoft Azure ML is a fully-managed cloud service enabling data aware developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.

Join us for a practical insight into the fascinating world of Machine Learning where you can feel significantly different but never certain, where deviation is normal, and you will be amongst like-minded friends. No PhD in statistics required!

Our Microsoft AzureML event is a deep dive into the considerable power of this program. So…

1. Bring your laptop.

2. Sign up for a free (30 day) Azure ML Studio account using your Microsoft Live ID: https://studio.azureml.net/

3. Download the document we will follow in the session: https://onedrive.live.com/view.aspx?cid=45a80d424efe914a&page=view&resid=45A80D424EFE914A!18367&parId=45A80D424EFE914A!8718&authkey=!AO-VMPL82qtb_JE&app=Word&wacqt=undefined

Who’s talking…
Andrew Fryer
Technical Evangelist at Microsoft UK, specialising in database management & BI. When not blogging and making screencasts, he can be found presenting at various technical events across the UK including, Future Decoded, TechDays OnLine, and any event with the acronym SQL in the title.
Bianca Furtuna
Technical Evangelist at Microsoft UK, currently focusing on the Azure Data Platform and IoT. During her Electrical and Electronic Engineering degree at Imperial College, her main interests were in Artificial Intelligence and Machine Learning, Control Systems and Signal Processing and she has built on this since with spells at IBM, ARM and Citi. As a Technical Evangelist, Bianca is engaging with technical audiences across the UK delivering presentations, workshops and technical advice. Please note:

This event starts at 8pm, after the How do you Make a DataScientist event. It may run long so plan for a late finish.

Thanks to Arvindra Sehmi of Oxford Economics for making this event happen.