I need our systems to think. I need them to learn and I need them to present issues and problems and anomalies to the employees, to the managers. Adam.

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Presentation transcript:

I need our systems to think. I need them to learn and I need them to present issues and problems and anomalies to the employees, to the managers. Adam Coffey President and CEO WASH Laundry Systems What is Machine Learning Computing systems that become smarter with Experience “Experience” = past data + human input “ ”

Descriptive analytics Diagnostic analytics Predictive analytics Prescriptive analytics What happened? Why did it happen? What will happen? How can we make it happen? Traditional BI Advanced Analytics INFORMATION IMPROVEMENT

GOALS Competitiveness Uptime and Satisfaction Costs SOLUTION Connected Asset Monitoring Platform with Power BI and Azure Machine Learning Real Time Performance dashboards (mobile, pc, …) Predictive downtime analysis and Prescriptive maintenance OUTCOMES Significantly Improved uptime and reliability Reduced Costs for Thyssen Krupp and its customers

Vision Analytics Recommenda- tion engines Advertising analysis Weather forecasting for business planning Social network analysis Legal discovery and document archiving Pricing analysis Fraud detection Churn analysis Equipment monitoring Location-based tracking and services Personalized Insurance Advanced Analytics are core capabilities that can bring huge value for your business & administrations What can Machine Learning do for you…?

Croatian Health Insurance Fund Predictive Analytics projects to prevent hospital frauds 3 steps 1.Envision concept and identify scenarios 2.Prove that it worked (POC) 3.Fine tune, extend and roll out Key Outcomes 1.Increased accuracy of Fraud Detection 2.Reduce costs and manual treatment 3.(next step) fraud prevention 4.Further scenarios identified (Pharmacies)

Huge set-up costs of tools, expertise, and compute/storage capacity Siloed and cumbersome data management restricts access to data Complex and fragmented tools limit Data exploration and model definition Many models never achieve business value due to difficulties with deployment Expensive Siloed data Disconnecte d tools Deployment complexity Break away from limitations

Fully managed Connected Best in Class Algorithms (+ R + Python) Deploy in minutes No software to install, No hardware to manage, One portal to view and update Simple drag, drop and connect interface for both data acquisition and modeling Sample experiments, tested algorithms, support for custom R Tooled for quick deployment, hand-off and updates – click “Publish Web Service”

“ Empower every people and organization on the planet to achieve more ” Select a business goal Prepare your data Conduct a Pilot Iterate, bring value and achieve More