Advancing Research through Machine Learning -- Supervised Machine Learning for the Chemical Sciences -- Linear Models, Kernels, and Trees -- Representations of Atomistic Systems -- Neural Networks and Learned Representations -- Applying Machine Learning Models in Chemistry
Summary
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
Notes
Online resource; title from resource web page (viewed August 18, 2020)
