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Nueral Network
Nueral Network
Nueral Network
Nueral Network
Nueral Network
Nueral Network
Nueral Network
Nueral Network
Nueral Network
Nueral Network
Nueral Network
Nueral Network
Nueral Network
Nueral Network
Nueral Network
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Nueral Network

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  • 1. Kohinoor business school Kohinoor business school MMS -1A 2011 - 2013 Information Technology Management 01
  • 2. Presented by: Akhilesh pillai Anchal Chowdhari Ankit Sanghavi Ankita Varadkar SUBMITTED TO: Manjiri Karandikar 02
  • 3. NUERAL NETWORKS 03
  • 4. history Alexander Bain (1873). William James(1890).C. S. Sherrington (1898) conducted experiments totest James’s theory.McCullouch and Pitts(1943) created a computationalmodel for neural.Farley and Clark (1954) first used computationalmachines. 04
  • 5. what it does? Recognition & identification Data mining Monitoring & control Forecasting & prediction 05
  • 6. what is the need of neural network? Failure to extract meaning from complex and imprecise data. Sequential batch processing of data is inadequate. Need to replace the conventional approach to define. algorithms 06
  • 7. business application Medical sector Biomedical system Inststant phycisian Electronic nose 07
  • 8. business application Preventing & detecting fraud Establishing credit worthiness Predicting default/bankruptcy Marketing application 08
  • 9. other usage of neural networks Recognition of speaker in communicaton Diagnosis of hepatit is Texture analysis Three dimensional object recognition Handwritten word recgnition 9
  • 10. benefits of neural network Neurobiological Analogy Fault Tolerance Self Repair Adaptivity 10
  • 11. criticism of neural network  large diversity of training for real-world operation  Time Consuming  Require of very High Power RAM & HD
  • 12. vendors Microsoft (excel)-Neural tools Nuenet pro Cacsci –brainmaker Matlab-neural network toolbox 12
  • 13. prices From free trial versions to &499 & up. Nueral network toolbox requires matlab, more costly to implement if the company does not already use matlab. 13
  • 14. conclusion There are many possible business applications for neural networks. Any application that could benefit from tracking past behaviour patterns & using them to predict future behaviour is a candidate for a neural network. We only explored some of the uses of neural networks. 14
  • 15. 15

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