PPT-Data Mining and Predictive Analytics Toolkit

Author : danika-pritchard | Published Date : 2017-08-25

December 2013 Jakub Miarka University of Leeds RapidMiner Formerly called YALE Yet Another Language Environment Environment for machine learning data and text

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Data Mining and Predictive Analytics Toolkit: Transcript

December 2013 Jakub Miarka University of Leeds RapidMiner Formerly called YALE Yet Another Language Environment Environment for machine learning data and text mining predictive and business analytics. Seayoung. Rhee. Sr. Technical Product Manager. Microsoft Advanced Analytics. BRK2569. Transformational . trends. cloud . computing. 2011 .  2016 5x increase. e. merging data science talent. Universities filling . San Francisco. , February 19, 2009. The Unrealized Power of Data. Andreas Weigend. people & data. Outline. Q: Current bottleneck for you in your business? (Scarce . vs. abundant)?. Historical perspective. Predictive Modeling. . . encompasses a variety of techniques to analyze current and historical facts to make predictions about future events.. Predictive models . exploit patterns . found in historical and transactional data . (CS40003). Dr. Debasis Samanta. Associate Professor. Department of Computer Science & Engineering. Lecture #11. Sensitivity Analysis. Topics Covered in this Presentation. Introduction. Estimation Strategies. Brian Z. Brown, FCAS, MAAA. Principal and Consulting Actuary. Stan Smith. Predictive Analytics Consultant . April 29, 2016. Advancements In Reserving. Use of stochastic methods.. . Advancements in computing power have allowed for more sophisticated reserving methodologies. Techniques . for Effective Prevention Programs. Raj Nagaraj, Ph.D. . Chief Technology Officer. Deccan International. OUTLINE. About Deccan. CRR And Predictive Modelling . Techniques. Predictive Modelling And Other Techniques (PM) . Bo Sundgren. Senior professor, Dalarna University. Keynote speaker NTTS 2017. mailto: . bo.sundgren@gmail.com. . website: . https://sites.google.com/site/bosundgren/. . Contents. Three examples of applications. Prof Sunil . Wattal. Agenda. Introductions. Intro to Data Analytics. Course Logistics. Overview of Topics. Setting up SAS EM. Data Analytics. McKinsey Report. s. hortage of 1.5 million analytics individuals in US. How U.S. companies can improve ERM by using Advanced techniques developed for solvency II and emerging predictive analytics methods. Howard Zail, FSA, FFA, MAAA. Partner, . Elucidor. , LLC. hzail@elucidor.com. is the use of:. data, . information technology, . statistical analysis, . quantitative methods, and . mathematical or computer-based models . to help managers gain improved insight about their business operations and . C. ultural . E. ntrepreneurship. @. andyhamflett. WHY AM I HERE?. DATA = BAD. DATA = BAD. DATA = BAD. DATA = MISUNDERSTOOD?. SESSION OUTLINE. SESSION OUTLINE. SESSION OUTLINE. BIG DATA – QUÉ?. @AAM_Associates @andyhamflett . Coping with uncertain futures. Dr Christophe Lazaro (. UCLouvain. ). Dr Marco Rizzi (UWA Law School). Introduction – technological context. development of artificial intelligence (AI) and digitization of life . 1. UNOS Labs. 2. UPDATE: Understanding CIT Project. 3. Components of CIT . (not to scale). 4. Procurement. Transit. Transplant. Clamp Time. Departure. Offer . Acceptance. Delivery Time. Transplant Time. Course/Research Topics. Material derived from other sources and “Mining Massive Datasets” from:. Jure Leskovec, . Anand. . Rajaraman. , Jeff Ullman . Stanford University. http://www.mmds.org . Fayé A. Briggs, PhD.

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