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Morten Hjorth-Jensen
2023-08-21 09:54:36 +02:00
parent 461cc4bf54
commit 3641bfd81e
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doc/src/week34/beamerweek34.do.txt
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@@ -118,7 +118,8 @@ In addition to the lecture notes, we recommend the books of Bishop, Hastie et al
!bblock
* "Goodfellow, Bengio, and Courville (GBC), Deep Learning":"https://www.deeplearningbook.org/"
* Christopher M. Bishop (CB), Pattern Recognition and Machine Learning
* Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer, URL:"https://www.springer.com/gp/book/9780387848570".* Aurelien Geron (AG), 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 and hands-on applications of all algorithms discussed in this course.
* "Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer":"https://www.springer.com/gp/book/9780387848570".
* "Aurelien Geron (AG), 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 and hands-on applications of all algorithms discussed in this course.
* "Kevin Murphy (KM), Probabilistic Machine Learning, an Introduction":"https://probml.github.io/pml-book/book1.html"
!eblock
doc/src/week34/week34.do.txt
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@@ -116,7 +116,7 @@ In addition to the lecture notes, we recommend the books of Bishop, Hastie et al
!bblock
* "Goodfellow, Bengio, and Courville (GBC), Deep Learning":"https://www.deeplearningbook.org/"
* Christopher M. Bishop (CB), Pattern Recognition and Machine Learning
* "Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer, URL:"https://www.springer.com/gp/book/9780387848570".
* "Hastie, Tibshirani, and Friedman (HTF), The Elements of Statistical Learning, Springer":"https://www.springer.com/gp/book/9780387848570".
* "Aurelien Geron (AG), 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 and hands-on applications of all algorithms discussed in this course.
* "Kevin Murphy (KM), Probabilistic Machine Learning, an Introduction":"https://probml.github.io/pml-book/book1.html"
!eblock