Wisdom 2018 Presentations

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Jeff Dwyer from ezCater discusses how they use RapidMiner to detect the lifetime value of a customer early on in this presentation.

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Munwar Shariff from Cappius Technologies / Anblicks demonstrates how RapidMiner can help financial institutions increase revenues and reduce business risk with valuable insights about their customers.

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The hype around data science produces a dense fog that can easily restrict the broad scope of your vision, the rising slope of your applications, and the promised hope of new opportunities. This presentation busts those myths and shows you a better, simpler, and more rapid path to value and insights from your data.

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Learn about basic concepts of Deep Learning and scenarios that might benefit from its usage, with guidelines for creating networks in a visual way and tips for optimization.

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Learn how the Data Scientists teams and IT organization partnered at HPE, providing tools, technologies and processes to close the skill set gap between data science and business roles.

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The Pegasus Group Company discusses how they monitor and detect the presence of certain pathogens in the oceanic water, alerting the corresponding entities to take action and prevent the spread of these pathogens.

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VigiLanz has adopted RapidMiner to integrate machine learning and advanced analytics into its top-ranked clinical decision support suite to detect sepsis early.

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This presentation gives an overview of predictive analytics use cases at Lufthansa with some practical use cases from the airline industry like the prediction of arrival times.

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This presentation outlines use cases from pure real time reporting to applying predictive analytics. For each use case we will show how they can be implemented using the Streaming Extension and the RapidMiner platform.

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This presentation discusses Verizon’s Outlier detection system, which uncovers anomalies and then allows for a deep-dive into actionable insights.

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This presentation covers typical data science roadblocks and how to overcome them, the optimal project structure and timeline for a data science project, and cross-industry examples and success stories of businesses at varying levels of data sophistication.

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Ingo discusses the need for anew approach to data science, machine learning, and artificial intelligence. Automated machine learning needs to guide analysts and not overrule their decisions.

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Master Loyalty Group presents how they created a recommendation system within RapidMiner and the benefits they have seen from doing so.

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This presentation covers how data science tools can be used to advance your process improvement efforts. From HR, Quality, R&D to Finance, data analytics can (and should) be applied internally.

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This presentation covers how to use sentiment analysis to extract value from context-laden text in a fast, reliable, and objective manner.

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This presentation shows how to leverage machine learning to detect and prevent fraud and make fraud fighters more efficient and effective.

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This session presents a case study demonstrating a risk-based investment decision-making approach supported by machine learning for water distribution system assets.

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This session will walk you through how to use RapidMiner and Text Mining on customer service call transcripts.

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