Machine Learning in Chemistry
- ISBN-10
- 0841299005
- ISBN-13
- 9780841299009
- Series
- Machine Learning in Chemistry
- Category
- Science
- Language
- English
- Published
- 2020-05-28
- Publisher
- American Chemical Society
- Authors
- Jon Paul Janet, Heather J. Kulik
Description
Recent advances in machine learning or artificial intelligence for vision and natural language processing that have enabled the development of new technologies such as personal assistants or self-driving cars have brought machine learning and artificial intelligence to the forefront of popular culture. The accumulation of these algorithmic advances along with the increasing availability of large data sets and readily available high performance computing has played an important role in bringing machine learning applications to such a wide range of disciplines. Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemists. Machine Learning in Chemistry focuses on the following to launch your understanding of this highly relevant topic: Topics most relevant to chemical sciences are the focus. Focus on concepts rather than technical details. Comprehensive referencing provides sources to go to for more technical details. Key details about methods that underlie machine learning (not easy, but important to understand the strengths as well as the limitations of these methods and to identify where domain knowledge can be most readily applied. Familiarity with basic single variable calculus and in linear algebra will be helpful although we have provided step-by-step derivations where they are important
Get the book
Other editions
-
- 2020-07-15
- 546 pages
- Ebook
- Royal Society of Chemistry
Similar books
-
Machine Learning in Chemistry: Data-Driven Algorithms, Learning Systems, and Predictions
By Edward O. Pyzer-Knapp, Teodoro LainoAtomic-scale representation and statistical learning of tensorial properties -- Prediction of Mohs hardness with machine learning methods using compositional features -- High-dimensional neural network potentials for atomistic simulations - ...
-
Deep Learning for the Life Sciences: Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More
By Patrick Walters, Bharath Ramsundar, Peter EastmanThis practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields.
-
Quantum Chemistry in the Age of Machine Learning
By Pavlo O. DralDrawing on the expertise of a team of specialist contributors, this book serves as a valuable guide for both aspiring beginners and specialists in this exciting field.
-
Machine Learning in Chemistry
By Edward O. Pyzer-Knapp, Teodoro Laino"Sponsored by the ACS Division of Computers in Chemistry."
-
Artificial Intelligence in Chemistry
By José S. Torrecilla, John C. Cancilla, Jose Omar ValderramaArtificial Intelligence in Chemistry
-
Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling
By Jahan B. GhasemiDrawing on the knowledge of a global team of researchers, this book will be a helpful guide for chemists interested in developing their skills in multivariate data and error analysis.
-
Data Science in Chemistry: Artificial Intelligence, Big Data, Chemometrics and Quantum Computing with Jupyter
By Thorsten GresslingThis book focuses on chemistry, explaining how to use data science for deep insights and take chemical research and engineering to the next level. It covers modern aspects like Big Data, Artificial Intelligence and Quantum computing.
-
Artificial Intelligence in Drug Discovery
By Nathan BrownProviding a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.
-
Computational and Data-Driven Chemistry Using Artificial Intelligence: Fundamentals, Methods and Applications
By Takashiro AkitsuDrawing on the knowledge of its expert team of global contributors, the book offers fascinating insight into this rapidly developing field and serves as a great resource for all those interested in exploring the opportunities afforded by ...
-
Reviews in Computational Chemistry
By Kenny B. Lipkowitz, Abby L. ParrillThe Reviews in Computational Chemistry series brings together leading authorities in the field to teach the newcomer and update the expert on topics centered on molecular modeling. • Provides background and theory, strategies for using ...