From ec0753ec8ab76191d8684aa1d9f99e132b29cf7b Mon Sep 17 00:00:00 2001 From: NinaM31 <57009004+NinaM31@users.noreply.github.com> Date: Sun, 18 Apr 2021 03:17:54 +0300 Subject: [PATCH] added a Book: Mathematics for machine learning --- README.md | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 7c82509..5ee3788 100644 --- a/README.md +++ b/README.md @@ -40,12 +40,13 @@ 7. [Artificial Intelligence: A Modern Approach](http://aima.cs.berkeley.edu/) 8. [Deep Learning in Neural Networks: An Overview](http://arxiv.org/pdf/1404.7828v4.pdf) 9. [Artificial intelligence and machine learning: Topic wise explanation](https://leonardoaraujosantos.gitbooks.io/artificial-inteligence/) -10.[Grokking Deep Learning for Computer Vision](https://www.manning.com/books/grokking-deep-learning-for-computer-vision) +10. [Grokking Deep Learning for Computer Vision](https://www.manning.com/books/grokking-deep-learning-for-computer-vision) 11. [Dive into Deep Learning](https://d2l.ai/) - numpy based interactive Deep Learning book 12. [Practical Deep Learning for Cloud, Mobile, and Edge](https://www.oreilly.com/library/view/practical-deep-learning/9781492034858/) - A book for optimization techniques during production. 13. [Math and Architectures of Deep Learning](https://www.manning.com/books/math-and-architectures-of-deep-learning) - by Krishnendu Chaudhury 14. [TensorFlow 2.0 in Action](https://www.manning.com/books/tensorflow-in-action) - by Thushan Ganegedara - +15. [Mathematics for Machine Learning](https://mml-book.github.io/book/mml-book.pdf) - by Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong + ### Courses 1. [Machine Learning - Stanford](https://class.coursera.org/ml-005) by Andrew Ng in Coursera (2010-2014)