| Description |
1 online resource (29 pages) : color illustrations |
| Physical Medium |
polychrome |
| Description |
text file |
| Bibliography |
Includes bibliographical references (page 29). |
| Contents |
Introduction -- Machine learning challenges -- The future of machine learning -- Appendix. |
| Summary |
"The field of machine learning continues to advance at a rapid pace owing to increased computing power, better algorithms and tools, and greater availability of data. Machine learning is now being used in a range of applications, including transportation and developing automated vehicles, healthcare and understanding the genetic basis of disease, and criminal justice and predicting recidivism. As the technology advances, it promises additional applications that can contribute to individual and societal well-being. The Raymond and Beverly Sackler U.S.-U.K. Scientific Forum "The Frontiers off Machine Learning" took place on January 31 and February 1, 2017, at the Washington, D.C., headquarters of the National Academies of Sciences, Engineering, and Medicine. Participants included industry leaders, machine learning researchers, and experts in privacy and the law, and this report summarizes their high-level interdisciplinary discussions"--Publisher's description |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Machine learning -- Congresses.
|
|
Machine learning. |
| Genre/Form |
Electronic books.
|
|
Congress.
|
|
Conference papers and proceedings.
|
|
Conference papers and proceedings.
|
| Added Author |
National Academies of Sciences, Engineering, and Medicine (U.S.), issuing body.
|
|
Royal Society (Great Britain), author.
|
|
Sackler Forum (2017 : Newport Pagnell, England), author.
|
| Other Form: |
Print version: Society, The Royal. Frontiers of Machine Learning : 2017 Raymond and Beverly Sackler U.S.-U.K. Scientific Forum. Washington, D.C. : National Academies Press, ©2018 9780309471947 |
| ISBN |
9780309471978 (electronic book) |
|
0309471974 (electronic book) |
|
9780309471954 |
|
0309471958 |
|
9780309471947 |
|
030947194X |
|
