From 0b5c25a5f5d0d50928c8f8b247723a0a0d104735 Mon Sep 17 00:00:00 2001 From: Morten Hjorth-Jensen Date: Sat, 19 Jun 2021 21:35:02 +0200 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index c6f68074e..7ab674a17 100644 --- a/README.md +++ b/README.md @@ -183,7 +183,7 @@ The lecture notes are collected as a jupyter-book at https://compphysics.github. the books of Bishop and Goodfellow et al. We will follow these texts closely and the weekly reading assignments refer to these two texts. - Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer, https://www.springer.com/gp/book/9780387310732. This is the main textbook and this course covers chapters 1-7, 11 and 12. - We recommend also the text of Ian Goodfellow and Yoshua Bengio and Aaron Courville. The different chapters are available for free at https://www.deeplearningbook.org/. Chapters 2-14 are highly recommended. - +The weekly plans will include reading suggestions from these two textbooks. _Additional textbooks_: - Trevor Hastie, Robert Tibshirani, Jerome H. Friedman, The Elements of Statistical Learning, Springer, https://www.springer.com/gp/book/9780387848570. This is a well-known text and serves as additional literature. - Aurelien Geron, Hands‑On Machine Learning with Scikit‑Learn and TensorFlow, O'Reilly, https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/. This text is very useful since it contains many code examples.