MecaNano Member and WG4 co-lead, Stefan Sandfeld, has published a new book titled “Materials Data Science — Introduction to Data Mining, Machine Learning, and Data-Driven Predictions for Materials Science and Engineering.”
The book is aimed for Material Science students in their first Masters of Science semesters and PhD students or scientists who haven’t had much contact with machine learning and data science or want to deepen their knowledge. One unique aspect is that all ML/DL methods are explained and implemented in detail. There are numerous Python examples, many of them directly relevant for materials science or physics. The book assumes some Python experience; but it focuses more on clarity instead of very compact and elegant code.
You can get the book from Springer at https://link.springer.com/book/10.1007/978-3-031-46565-9.
There is a 40% discount during the initial period (use coupon code: MRSMEMBER) if your institute does not have a “standard Springer subscription”. You do not need to be a member of MRS to use the code.
And of course, the book also comes with a webpage and code examples for machine learning (http://mds-book.org/) – this has the links to Springer as well as to the open source repositories with datasets and code.
Springer has a 50% discount until 4 July for all hardcovers (coupon code: 50FLASH)