1. The document discusses Kohinoor Business School's MMS program from 2011-2013, presented by several students on the topic of neural networks. 2. It provides a brief history of neural networks and describes their ability to recognize and identify patterns in complex data through processes like data mining and prediction. 3. Examples of business applications for neural networks discussed include medical diagnosis, fraud detection, credit analysis, and marketing. The conclusion notes neural networks' potential usefulness for applications involving behavior pattern recognition and prediction.

1. Kohinoor business school
Kohinoor business school
MMS -1A
2011 - 2013
Information Technology Management
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2. Presented by:
Akhilesh pillai
Anchal Chowdhari
Ankit Sanghavi
Ankita Varadkar
SUBMITTED TO:
Manjiri Karandikar
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3. NUERAL NETWORKS
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4. history
 Alexander Bain (1873).
 William James(1890).
C. S. Sherrington (1898) conducted experiments to
test James’s theory.
McCullouch and Pitts(1943) created a computational
model for neural.
Farley and Clark (1954) first used computational
machines.
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5. what it does?
Recognition & identification
Data mining
Monitoring & control
Forecasting & prediction
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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
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7. business application
Medical sector
Biomedical
system
Inststant
phycisian
Electronic
nose
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8. business application
Preventing & detecting fraud
Establishing credit worthiness
Predicting default/bankruptcy
Marketing application
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9. other usage of neural networks
Recognition of speaker in communicaton
Diagnosis of hepatit is
Texture analysis
Three dimensional object recognition
Handwritten word recgnition
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10. benefits of neural network
Neurobiological Analogy
Fault Tolerance
Self Repair
Adaptivity
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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
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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.
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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.
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