| dc.contributor.advisor | Michael A. M. Davies. | en_US |
| dc.contributor.author | Shukla, Ritesh | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Engineering Systems Division. | en_US |
| dc.date.accessioned | 2017-03-10T15:06:13Z | |
| dc.date.available | 2017-03-10T15:06:13Z | |
| dc.date.copyright | 2014 | en_US |
| dc.date.issued | 2014 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1721.1/107342 | |
| dc.description | Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, System Design and Management Program, 2014. | en_US |
| dc.description | Cataloged from PDF version of thesis. | en_US |
| dc.description | Includes bibliographical references (pages 48-50). | en_US |
| dc.description.abstract | As interest for adopting machine learning as a core component of a business strategy increases, business owners face the challenge of integrating an uncertain and rapidly evolving technology into their organization, and depending on this for the success of their strategy. The field of Machine learning has a rich set of literature for modeling of technical systems that implement machine learning. This thesis attempts to connect the literature for business and technology and for evolution and adoption of technology to the emergent properties of machine learning systems. This thesis provides high-level levers and frameworks to better prepare business owners to adopt machine learning to satisfy their strategic goals. | en_US |
| dc.description.statementofresponsibility | by Ritesh Shukla. | en_US |
| dc.format.extent | 50 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 | Institute for Data, Systems, and Society. | en_US |
| dc.subject | System Design and Management Program. | en_US |
| dc.subject | Engineering Systems Division. | en_US |
| dc.title | Machine learning ecosystem : implications for business strategy centered on machine learning | en_US |
| dc.title.alternative | Implications for business strategy centered on machine learning | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | S.M. in Engineering and Management | en_US |
| dc.contributor.department | System Design and Management Program. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Engineering Systems Division | |
| dc.contributor.department | Massachusetts Institute of Technology. Institute for Data, Systems, and Society | |
| dc.identifier.oclc | 972910121 | en_US |