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- 1. The Physics of Everyday Life Bayesian Neural Networks in Business Applications Big Data User Group – July 2013 Meetup in Karlsruhe Dr. F. Wick, Blue Yonder GmbH & Co. KG felix.wick@blue-yonder.com
- 2. Our Background: High Energy Physics Fundamental research at the forefront of science A few key questions in High Energy Physics: » Our current theoretical understanding is called the “Standard Model” » Extremely well tested, some of its aspects have the most precise agreement between theoretical predictions and experimental results across all sciences » What happened at the beginning of the universe? » Does our theory remain valid under such extreme conditions or is it a “low energy approximation” of a more fundamental theory? » What is the origin of mass? A Higgs boson has been found » Is it the Higgs boson? » Why is there so much matter left in the universe? » All matter should have annihilated with anti-matter, where does this asymmetry come from? Photo: CERN DI-2-8-91 The Physics of Everyday LifeJuly 20132
- 3. The Large Hadron Collider at CERN Built to understand how exactly our universe works Schreiben Sie hier Ihren Text LHC: 27km circumference Photo: CERN The Physics of Everyday LifeJuly 20133
- 4. Big Data in Particle Physics At the LHC (CERN) - per experiment: • 40 000 000 events per second • up to 1 PetaByte per second raw data • 1 PB of data get stored per year searching for the needle in the hay stack… Need to filter out the „interesting“ events in real-time Photo: CERN The Physics of Everyday LifeJuly 20134
- 5. Artificial Neural Networks and NeuroBayes The Physics of Everyday Life ► NeuroBayes classification core based on simple feed forward neural network ► Information coded in connections between neurons ► Each neuron performs fuzzy decisions ► Neural networks learn from examples ► Human brain: about 1011 neurons about 1014 connections ► NeuroBayes: 10 to few 100 neurons July 20135
- 6. Bayes‘ Theorem and NeuroBayes The Physics of Everyday Life Posterior Evidence Likelihood Prior ► NeuroBayes internally uses Bayesian arguments for regularisation ► NeuroBayes automatically makes Bayesian posterior statements July 20136
- 7. A little more Detail The Physics of Everyday LifeJuly 20137
- 8. Mode I: Classification Issues The Physics of Everyday Life Classification: Binary targets: Each single outcome will be “yes“ or “no“ NeuroBayes output is the Bayesian posterior probability that answer is “yes“ (given that inclusive rates are the same in training and test sample, otherwise simple transformation necessary). Examples: ► This elementary particle is a muon. ► Customer Meier will cancel his contract next year. July 20138
- 9. Probability density for real valued targets: For each possible (real) value a probability (density) is given. From that all statistical quantities like mean value, median, mode, standard deviation, etc. can be deduced. Mode II: Regression Issues The Physics of Everyday Life Examples: ► Energy of an elementary particle ► Turnaround of an article next year July 20139
- 10. Historic or simulated data Data set a = ... b = ... c = ... .... t = …! NeuroBayes® Teacher NeuroBayes® Expert New or real data Data set a = ... b = ... c = ... .... t = ? Expertise Expert system f t Probability that hypothesis is correct (classification) or probability density for variable t t How it works: Training and Prediction The Physics of Everyday LifeJuly 201310
- 11. What does the future hold? What would happen if... ... a large supermarket chain knew precisely how much fresh fruit it will sell? The Physics of Everyday LifeJuly 201311
- 12. Blue Yonder – forward looking, forward thinking Now about 100 employees of which most are post-docs, mainly from HEP. Doubling our numbers in 2012, 2013 is looking good… 3 Offices: Karlsruhe, Hamburg (Germany) London (UK) Started as a spin-off from the University of Karlsruhe, Germany supported by the Federal Ministry for Education and Research. The Physics of Everyday LifeJuly 201312
- 13. Use all available and relevant information as input, e.g. measurements from the various sub-detectors, … NeuroBayes will extract statistically significant patterns in the data to derive the prediction. Prediction will return the best estimator for a measurement including a statistically sound estimation of the expected spread. 100Energy Momentum Direction Type 50 90 Sub-Detector Distance 200 Calo Kaon ... propabilityP Particle Property E(X) NeuroBayes from Science to Industry Predictive Analytics in High Energy Physics The Physics of Everyday LifeJuly 201313
- 14. Use all available and relevant information as input, e.g. article properties, previous sales, etc NeuroBayes will extract statistically significant patterns in the data to derive the prediction. Prediction will return e.g. the most probable sales rate including a statistically sound estimation of the expected spread. Article size Picture size colour Previous sales M 21% red brand price 19,9 171 24 ... propabilityP Prediction sales E(X) NeuroBayes from Science to Industry Predictive Analytics in industry E.g. Retail NeuroBayes allows data-driven analysis and forecasts – both in science and industry The Physics of Everyday LifeJuly 201314
- 15. Automated replenishment in supermarkets Fondsmanagement Insurance: Risk prediction Fashion: Sales prediction Media Churn Management Artikelabsatz P E(X)=413 Stock Exchange Order Placement System SAP NeuroBayes® NeuroBayes from Science to Industry Predictive Analytics is the key to many industries The Physics of Everyday LifeJuly 201315
- 16. » Most conventional methods: Forecast is a single number » No estimate how precise this number is » Does not allow to handle asymmetric distribution of probabilities » NeuroBayes: Prediction of a full probability density distribution Asymmetric probability density distribution X1: most probable value (n.b. all other values may still occur) P (x) quantity(x) x1 Optimal estimate for your use-case X2: Median: 50% of all values are smaller, 50% larger than this x2 Get more from the Forecasts The Physics of Everyday LifeJuly 201316
- 17. Conclusion » Exploiting “Big data” is the next “big” challenge to advance industry » “In this war for customers, the ammunition is data — and lots of it […]” (G. Hawkings, Harvard Business Review, Sep. 2012) » This is the day and age of Predictive Analytics » Data-driven business instead of models and assumptions » Peta-bytes of data and machine learning techniques allow statistically sound analyses » Blue Yonder: From “Big Science” to “Big Business” » Background in High Energy Physics: Crossing the bridge from understanding the behaviour of the fundamental particles at the origin of the universe to the “Big Bang” in sales forecast, risk analysis, churn management, etc. » Versatile NeuroBayes machine learning solution allows to optimise a wide range of business cases The Physics of Everyday LifeJuly 201317
- 18. Thank you very much For your attention!
- 19. Disclaimer This Presentation (the Presentation) has been prepared by Blue Yonder GmbH & Co KG (collectively, with any officer, director, employee, advisor or agent of any of them, the Preparers) for the purpose of setting out certain confidential information in respect of Blue Yonder’s business activities and strategy. References to the “Presentation” includes any information which has been or may be supplied in writing or orally in connection with the Presentation or in connection with any further inquiries in respect of the Presentation. This Presentation is for the exclusive use of the recipients to whom it is addressed. This Presentation and the information contained herein is confidential. In addition to the terms of any confidentiality undertaking that a recipient may have entered into with Blue Yonder, by its acceptance of the Presentation, each recipient agrees that it will not, and it will procure that each of its agents, representatives, advisors, directors or employees (collectively, Representatives), will not, and will not permit any third party to, copy, reproduce or distribute to others this Presentation, in whole or in part, at any time without the prior written consent of Blue Yonder, and that it will keep confidential all information contained herein not already in the public domain and will use this Presentation for the sole purpose of setting out [familiarizing itself with] certain limited background information concerning Blue Yonder and its business strategy and activities. The foregoing confidentiality obligation shall be legally binding for the recipient infinitely. This Presentation is not intended to serve as basis for any investment decision. If a recipient has signed a confidentiality undertaking with Blue Yonder, this Presentation also constitutes Confidential Information for the purposes of such undertaking. While the information contained in this Presentation is believed to be accurate, the Preparers have not conducted any investigation with respect to such information. The Preparers expressly disclaim any and all liability for representations or warranties, expressed or implied, contained in, or for omissions from, this Presentation or any other written or oral communication transmitted to any interested party in connection with this Presentation so far as is permitted by law. In particular, but without limitation, no representation or warranty is given as to the achievement or reasonableness of, and no reliance should be placed on, any projections, estimates, forecasts, analyses or forward looking statements contained in this Presentation which involve by their nature a number of risks, uncertainties or assumptions that could cause actual results or events to differ materially from those expressed or implied in this Presentation. Only those particular representations and warranties which may be made in a definitive written agreement, when and if one is executed, and subject to such limitations and restrictions as may be specified in such agreement, shall have any legal effect. By its acceptance hereof, each recipient agrees that none of the Preparers nor any of their respective Representatives shall be liable for any direct, indirect or consequential loss or damages suffered by any person as a result of relying on any statement in or omission from this Presentation, along with other information furnished in connection therewith, and any such liability is expressly disclaimed. Except to the extent otherwise indicated, this Presentation presents information as of the date hereof. The delivery of this Presentation shall not, under any circumstances, create any implication that there will be no change in the affairs of Blue Yonder after the date hereof. In furnishing this Presentation, the Preparers reserve the right to amend or replace this Presentation at any time and undertake no obligation to update any of the information contained in the Presentation or to correct any inaccuracies that may become apparent. This Presentation shall remain the property of Blue Yonder. Blue Yonder may, at any time, request any recipient, or its Representatives, shall promptly deliver to Blue Yonder or, if directed in writing by Blue Yonder, destroy all confidential information relating to this Presentation received in written, electronic or other tangible form whatsoever, including without limitation all copies, reproductions, computer diskettes or written materials which contain such confidential information. At such time, all other notes, analyses or compilations constituting or containing confidential information in the recipient’s, or their Representatives’, possession shall be destroyed. Such destruction shall be certified to Blue Yonder by the recipient in writing. Neither the dissemination of this Presentation nor any part of its contents is to be taken as any form of commitment on the part of the Preparers or any of their respective affiliates to enter any contract or otherwise create any legally binding obligation or commitment. The Preparers expressly reserve the right, in their absolute discretion, without prior notice and without any liability to any recipient to terminate discussions with any recipient or any other parties. The distribution of this Presentation in certain jurisdictions may be restricted by law and, accordingly, recipients of this Presentation represent that they are able to receive this Presentation without contravention of any unfulfilled registration requirements or other legal restrictions in the jurisdiction in which they reside or conduct business. July 2013 The Physics of Everyday Life19

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