dc.contributor.advisor | Jeanne Ross. | en_US |
dc.contributor.author | Bhilegaonkar, Ajay | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Engineering Systems Division. | en_US |
dc.date.accessioned | 2017-03-20T19:41:27Z | |
dc.date.available | 2017-03-20T19:41:27Z | |
dc.date.copyright | 2016 | en_US |
dc.date.issued | 2016 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/107589 | |
dc.description | Thesis: 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.description | Cataloged from PDF version of thesis. | en_US |
dc.description | Includes bibliographical references (pages 76-79). | en_US |
dc.description.abstract | Machine 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.statementofresponsibility | by Ajay Bhilegaonkar. | en_US |
dc.format.extent | 80 pages | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.rights | MIT 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.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Engineering and Management Program. | en_US |
dc.subject | System Design and Management Program. | en_US |
dc.subject | Engineering Systems Division. | en_US |
dc.title | Machine learning and cognitive computing : a proposed framework to navigate the opportunities | en_US |
dc.type | Thesis | en_US |
dc.description.degree | S.M. in Engineering and Management | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Engineering and Management Program | en_US |
dc.contributor.department | System Design and Management Program. | en_US |
dc.identifier.oclc | 974706790 | en_US |