1 option
Machine learning for polymer informatics / Ying Li and Tianle Yue.
- Format:
- Book
- Author/Creator:
- Li, Ying, University of Wisconsin-Madison., author.
- Yue, Tianle, University of Wisconsin-Madison., author.
- Series:
- ACS in focus, 2691-8307.
- ACS in focus, 2691-8307
- Language:
- English
- Subjects (All):
- Machine learning--Industrial applications.
- Machine learning.
- Artificial intelligence--Industrial applications.
- Artificial intelligence.
- Polymers--Analysis--Automation.
- Polymers.
- Materials--Data processing.
- Materials.
- Materials science--Mathematical models.
- Materials science.
- Genre:
- Electronic books.
- Physical Description:
- 1 online resource : illustrations (some color).
- Place of Publication:
- Washington, DC, USA : American Chemical Society, 2024.
- Summary:
- "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."-- Provided by publisher.
- Contents:
- Polymers and Polymer Informatics
- Advancing Research through Machine Learning (ML)
- Making Computers "Understand" Polymers
- Using Supervised Learning and Associated Datasets to Predict Polymer Properties
- Properties Prediction for Polymers with Different ML Models
- Applications of Unsupervised Learning and Explainable ML in Polymer Informatics
- Generate Hypothetical Polymer Structures Using ML Techniques.
- Notes:
- Includes bibliographical references and index.
- Local Notes:
- American Chemical Society, ACS In Focus eBooks - 2024 Front Files.
- ISBN:
- 9780841296350
- Access Restriction:
- Restricted for use by site license.
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.