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dc.contributor.advisorJeanne Ross.en_US
dc.contributor.authorBhilegaonkar, Ajayen_US
dc.contributor.otherMassachusetts Institute of Technology. Engineering Systems Division.en_US
dc.date.accessioned2017-03-20T19:41:27Z
dc.date.available2017-03-20T19:41:27Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/107589
dc.descriptionThesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, Engineering and Management Program, 2016.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 76-79).en_US
dc.description.abstractMachine Learning and Cognitive Computing universe is buzzing again. Recent significant events are special. There is also talk about beginning of a general purpose "Smart Machine Age" Advances in computing power, storage capacity and machine learning / cognitive computing technologies have a gained critical mass. This combination is driving significant growth and heavy investments. Cognitive computing is coming of age, the market is experiencing exponential growth and there are literally thousands of startups competing to seize the opportunities and hundreds of products hitting the market every quarter. Businesses definitely need to pay attention. But for a business professional, there is so much happening out there that, it is extremely hard to decide which way to turn. CC/ML opportunities may have huge potential to improve business performance or there may be opportunities to waste money. This is a major concern for large businesses and business professionals. This thesis aims to develop an end to end framework to navigate CC/ML opportunities. The framework will guide a business professional to navigate the complex landscape of CC/ML and arrive at a solution approach recommendation.en_US
dc.description.statementofresponsibilityby Ajay Bhilegaonkar.en_US
dc.format.extent80 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering and Management Program.en_US
dc.subjectSystem Design and Management Program.en_US
dc.subjectEngineering Systems Division.en_US
dc.titleMachine learning and cognitive computing : a proposed framework to navigate the opportunitiesen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Engineering and Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering and Management Program.en_US
dc.contributor.departmentSystem Design and Management Program.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division.en_US
dc.identifier.oclc974706790en_US


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