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

Bibliographic Details
Corporate Author:	American Chemical Society. Division of Computers in Chemistry (sponsoring body.)
Other Authors:	Pyzer-Knapp, Edward O. (Editor), Laino, Teodoro (Editor)
Format:	eBook
Language:	English
Published:	Washington, DC : American Chemical Society, 2019.
Series:	ACS symposium series ; 1326.
Subjects:	Machine learning. Chemisty > Computer programs. Chemistry > Computer simulation. Statistical hypothesis testing > Computer programs. Chemistry > Statistical methods > Computer programs. Chemistry > Molecular aspects > Statistical methods > Computer programs. Hardness > Forecasting > Computer programs. Neural networks (Computer science) Chemical reactions > Forecasting > Computer simulation. Drugs > Research > Computer simulation. Paradigm (Theory of knowledge) > Computer simulation. Learning by discovery > Computer simulation. Machine Learning. Chemistry > education. Statistics as Topic. Hardness. Neural Networks, Computer. Pharmaceutical Preparations > analysis. Computer Simulation. SCIENCE / Chemistry / Computational & Molecular Modeling. Electronic books. COMPUTERS / Data Science / Machine Learning.
Online Access:	Connect to the full text of this electronic book