國立虎尾科技大學 |

Machine learning for polymer informatics

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Machine learning for polymer informatics / Ying Li and Tianle Yue.
Author:	Li, Ying,
other author:	Yue, Tianle,
Description:	1 online resource :illustrations (some color). :
Subject:	SCIENCE / Chemistry / Computational & Molecular Modeling. -
Online resource:	https://dx.doi.org/10.1021/acsinfocus.7e8007
ISBN:	9780841296350

Machine learning for polymer informatics
Li, Ying,

Machine learning for polymer informatics [electronic resource] /Ying Li and Tianle Yue. - 1 online resource :illustrations (some color). - ACS in focus,2691-8307. - ACS in focus,.

Includes bibliographical references and index.

Polymers and Polymer Informatics --

"Machine learning has significantly accelerated the development of new polymer materials. Machine Learning for Polymer Informatics introduces the reader to the most popular ways of applying machine learning in polymer informatics. This primer will equip the reader to ask the right questions about the application of machine learning in their areas of interest, as well as critically interpret publications leveraging machine learning methods. The authors encourage readers to try machine learning techniques when they have sufficient data in their area of interest. The development of machine learning has far exceeded human imagination, and with sufficient data, everything is full of possibilities."--

ISBN: 9780841296350

Standard No.: 10.1021/acsinfocus.7e8007doiSubjects--Topical Terms:

1483756
SCIENCE / Chemistry / Computational & Molecular Modeling.
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: QD139.P6 / L56 2024eb

Dewey Class. No.: 547.7046

Machine learning for polymer informatics
LDR:02230nam a2200301 i 4500 001 1155766
003 DACS
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008 250627s2024 dcua ob 101 0 eng d
020 $a 9780841296350 $q electronic
024 7 # $a 10.1021/acsinfocus.7e8007 $2 doi
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035 $a 9780841296350
040 $a NjRocCCS $b eng $e rda $c NjRocCCS $d CaBNVSL
050 # 4 $a QD139.P6 $b L56 2024eb
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082 0 4 $a 547.7046 $2 23
100 1 $a Li, Ying, $e author. $u University of Wisconsin-Madison. $3 1483806
245 1 0 $a Machine learning for polymer informatics $c Ying Li and Tianle Yue. $h [electronic resource] /
264 1 $a Washington, DC, USA : $b American Chemical Society, $c 2024.
300 $a 1 online resource : $b illustrations (some color).
336 $a text $2 rdacontent
337 $a computer $2 rdamedia
338 $a online resource $2 rdacarrier
490 1 $a ACS in focus, $x 2691-8307
504 $a Includes bibliographical references and index.
505 0 0 $t Polymers and Polymer Informatics -- $t Advancing Research through Machine Learning (ML) -- $t Making Computers "Understand" Polymers -- $t Using Supervised Learning and Associated Datasets to Predict Polymer Properties -- $t Properties Prediction for Polymers with Different ML Models -- $t Applications of Unsupervised Learning and Explainable ML in Polymer Informatics -- $t Generate Hypothetical Polymer Structures Using ML Techniques.
520 # $a "Machine learning has significantly accelerated the development of new polymer materials. Machine Learning for Polymer Informatics introduces the reader to the most popular ways of applying machine learning in polymer informatics. This primer will equip the reader to ask the right questions about the application of machine learning in their areas of interest, as well as critically interpret publications leveraging machine learning methods. The authors encourage readers to try machine learning techniques when they have sufficient data in their area of interest. The development of machine learning has far exceeded human imagination, and with sufficient data, everything is full of possibilities."-- $c Provided by publisher.
590 $a American Chemical Society, ACS In Focus eBooks - 2024 Front Files.
650 # 7 $a SCIENCE / Chemistry / Computational & Molecular Modeling. $2 bisacsh $3 1483756
650 # 0 $a Materials science $x Mathematical models. $3 1004493
650 # 0 $a Materials $x Data processing. $3 910115
650 # 0 $a Polymers $x Analysis $x Automation. $3 1483808
650 # 0 $a Artificial intelligence $x Industrial applications. $3 796380
650 # 0 $a Machine learning $x Industrial applications. $3 805305
655 # 0 $a Electronic books. $2 local $3 554714
700 1 # $a Yue, Tianle, $e author. $u University of Wisconsin-Madison. $3 1483807
710 2 # $a American Chemical Society. $3 1436935
830 0 $a ACS in focus, $x 2691-8307. $3 1437890
856 4 # $u https://dx.doi.org/10.1021/acsinfocus.7e8007