Machine learning in chemistry : the impact of artificial intelligence [E-Book] / edited by Hugh M. Cartwright.
Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show significant potential across wide areas of science...
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Full text |
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Personal Name(s): | Cartwright, Hugh M., editor |
Imprint: |
Cambridge :
Royal Society of Chemistry,
2020
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Physical Description: |
1 online resource (546 pages) |
Note: |
englisch |
ISBN: |
1839160233 9781839160233 |
DOI: |
10.1039/9781839160233 |
Series Title: |
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Theoretical and computational chemistry ;
17 |
Subject (LOC): |
- Computers as Scientists
- How Do Machines Learn?
- MedChemInformatics: An Introduction to Machine Learning for Drug Discovery
- Machine Learning for Nonadiabatic Molecular Dynamics
- Machine Learning in Science – A Role for Mechanical Sympathy?
- A Prediction of Future States: AI-powered Chemical Innovation for Defense Applications
- Machine Learning for Chemical Synthesis
- Constraining Chemical Networks in Astrochemistry
- Machine Learning at the (Nano)materials-biology Interface
- Machine Learning Techniques Applied to a Complex Polymerization Process
- Machine Learning and Scoring Functions (SFs) for Molecular Drug Discovery: Prediction and Characterisation of Druggable Drugs and Targets
- Artificial Intelligence Applied to the Prediction of Organic Materials
- A New Era of Inorganic Materials Discovery Powered by Data Science
- Machine Learning Applications in Chemical Engineering
- Representation Learning in Chemistry
- Demystifying Artificial Neural Networks as Generators of New Chemical Knowledge: Antimalarial Drug Discovery as a Case Study
- Machine Learning for Core-loss Spectrum
- Autonomous Science: Big Data Tools for Small Data Problems in Chemistry
- Machine Learning for Heterogeneous Catalysis: Global Neural Network Potential from Construction to Applications
- A Few Guiding Principles for Practical Applications of Machine Learning to Chemistry and Materials