Machine learning in chemistry data-driven algorithms, learning systems, and predictions

Dettagli Bibliografici
Ente Autore:	American Chemical Society. Division of Computers in Chemistry (sponsoring body.)
Altri autori:	Pyzer-Knapp, Edward O. (Redattore), Laino, Teodoro (Redattore)
Natura:	Electronic Resource
Lingua:	English
Pubblicazione:	Washington, DC American Chemical Society [2019]
Serie:	ACS symposium series 1326
Soggetti:	Chemistry > Data processing. Machine learning. Electronic books.
Accesso online:	Available for University of the Philippines Diliman via ACS Publications. Click here to access Also available remotely for University of the Philippines Diliman via ACS Publications. Click here to access thru EZproxy