How to Use Machine Learning in Chemistry: An Introduction

Machine learning and artificial intelligence are hot topics across the sciences but what are they? How do machines learn and how can we apply them to problems in the chemical sciences?

Written as a primer for anyone new to the area of machine learning, this book provides an overview of the principles that underly its use in science and discusses its use as a practical tool in research. Readers will develop an understanding of key terminology and learn about the critical factors to be taken into account when using machine learning in science.

Drawing on examples from chemistry, this book covers topics including the mechanics of networks and training, representations in chemistry and solving issues with data. With a focus on practical implementation and how to ensure that your applications are robust, this is a fantastic starting point for anyone looking to incorporate machine learning into their work.

Hugh Cartwright is a computational chemist, now retired. He spent almost three decades as a member of the Chemistry Faculty at Oxford University in the U.K., where his research focussed on the application of Artificial Intelligence related methods to problems in science, using Artificial Neural Networks, Genetic Algorithms, Self-Organising Maps and Support Vector Machines. He has written or edited several texts on the use of Artificial Intelligence in science, including Applications of Artificial Intelligence in Chemistry, and Using Artificial Intelligence in Chemistry and Biology: a Practical Guide.