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Effective deployment and use of predictive models

April 29 @ 10:00 am - 11:00 am

This webinar will focus on how businesses and organisations that are already using some degree of advanced analysis and modelling can ensure that the insight and prediction derived from those efforts can actually be used to support effective decision-making in their day to day business operations.

In many respects the actual development of a predictive model is not the most challenging element of predictive analytics. The deployment of developed models can be a far more demanding challenge. Add to that the range and scope of available tools for model building. Today organisations have a dizzying array of choice ranging from open source tools and languages to commercial off the shelf software.

In this free online event we will explore and share approaches for effective model deployment in context where models and analytical routines have been developed using a range of different toolsets such as R, Python, SAS and IBM.

Who should attend?

This webinar will be of interest to you if you are a business analyst or a data scientist yourself, or if you lead or manage an analytical function in your organisation. You or your organisation need not be at an advanced stage with your analytical activities, although some level of familiarity with predictive analytics and modelling would be advantageous.

What topics will be covered?

This event will focus on the activities and approaches involved in the deployment stage of predictive analytics. Crucially, we will share best practice on how a model, regardless of the toolset or language in which it was developed, can be put to work to support decision making.

• Levels of modelling deployment – from the static “list” to real time scoring of your data
• Best practice for deploying models and modelling jobs within your organisation
• An overview of model deployment formats including native, SQL, PMML, C, executables/DLLs
• An introduction to batch deployment
• Overview of deployment platform options

Throughout the webinar each topic will be illustrated with live examples so you can see how organisations like yours are already using these techniques on real world data.

Book your free place now


April 29
10:00 am - 11:00 am
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