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June:Event Prediction with Azure Machine Learning. A Practical Training Co...
Tue. 13 June 2017, 9:00 am – 5:00 pm AEST
Event Prediction with Azure Machine Learning. A Practical Training Course.
Machine Learning is an exciting set of techniques that detect patterns from historical data to predict future events.
At first glance, the variety of decisions to prepare data and select algorithms to build a predictive model can seem overwhelming. However, practical guidance on how to make these decisions will demystify a lot of new terminology for the savvy data analyst and enable them to become a productive data scientist.
Presenting a unique training opportunity to move beyond retrospective dashboards, and start building meaningful data products for your business.
Focusing on classification techniques, this introductory course will provide hands-on examples of how to:
1. Prepare Data for a Predictive Model
2. Visualise Data for Discovery
3. Partition Data to Test and Validate a Model
4. Define meaningful features for your Model
5. Select the right Algorithms, Options and Parameters to Build a Classification Model
6. Evaluate the model's predictive performance
7. Put your model into real-world practice
This class includes practical labs utilising Azure Machine Learning, Power BI Desktop and an R Client to demonstrate the lifecycle of designing your first predictive solution.
If you currently have a role focused on data preparation and analysis and want to help your business make more informed decisions about what is likely to occur in the future, then this course is for you.
Hands-on Lab Prerequisites
You will need to bring along your own laptop and ensure the following:
1. Download and Install Power BI Desktop (https://powerbi.microsoft.com/en-us/desktop/)
· Windows 7 / Windows Server 2008 R2 or later
· .NET 4.5
· Internet Explorer 9 or later
· Memory (RAM):
At least 1 GB available, 1.5 GB or more recommended
At least 1440 x 900 or 1600 x 900 (16:9) recommended. Lower resolutions are not recommended as certain controls display beyond those resolutions
1 GHz or faster x86 or x64-bit processor recommended
**You will need to make sure WIFI access on your machine will support internet access during the session.
2. Download and Install R Client for Power
BI Desktop (https://powerbi.microsoft.com/en-us/documentation/powerbi-desktop-r-scripts/)