Learning Machine Learning, ML Books & Codes
See also:
Favoured

MLY (Andrew Ng), Machine Learning Yearning (EN full: ch113), 《CN: 机器学习秘籍》(CN Web online), (CN Github) and someone's notes: part 1 (bak), part 2 (bak) and part 3.

MLAPP (Kevin Murphy), Machine Learning  A Probablistic Perspective, is more comprehensive, insightful and interesting, and contains more "real" examples/problems. However, the presents are kinda out of order, which can be difficult to follow for a first book.

PRML (Christopher Bishop), Pattern Recognition and Machine Learning, is for the ones are very comfortable with calculus/linear algebra, Bayesoriented, advanced. (Github code in python, matlab)

ESL (Trevor Hastie), Elements of Statistical Learning, 2n ed. Springer 2017. Contains even harder math (ref: zhihu ans. > point.2), stats.oriented, advanced.
Good Text Books (for Master & PhD ?)
 Machine Learning by Peter Flach (Cambridge University Press 2012)  The Art and Science of Algorithms that Make Sense of Data. [The examples in this book are clear and easy to understand.]
 Machine Learning by Tom M Mitchell (McGrawHill 1997). (Classical, many original terms and ideas.)
 PRML by Christopher Bishop. (See "favoured")

南京大学 周志华 《机器学习》 (“西瓜书”) 清华大学出版社 2016：有伪码，但是比 Peter Flach 的难懂，需要比较熟悉统计语言，旁注格式不如他的另一本书《集成学习》中的 inline 注释。 类似清华的红皮 PR，没有推导过程，推导可以参考开源南瓜书：西瓜书的公式推导 (“南瓜书”) by Datawhale。
More Codes
 madhugnadig/MachineLearningAlgorithmsfromScratch 2018
 kaggle: Machine Learning Algorithms from Scratch 2020
Deep Learning
 Yoshua Bengio 和 GAN 之父 Ian Goodfellow 等人合著的 Deep Learning: 中文版 on github (pan.baidu), 英文版 github (pan.baidu).
 DL With Python, by Francois Chollet (also the author of Keras). Detailed introduction of CNN & RNN on CV & text analysis in Keras.
 DL for CV with Python [//trilogy], by Adrian Rosebrock.
 Hands on ML with SL and TF [//genius for clarity], by Aurélien Géron.
 DL  A Practioner's Approach, [java], by Adam Gibson & Josh Patterson.
 DL with Python, by Jason Brownlee. [//with code, easy to understand]
 Practical Python and Open CV, by Adrian Rosebrock. [// fast into CV]
 DL with TF, by Giancarlo Zaccone, [// DL 101].
More Books
 Pattern Classification by Richard O. Duda, David G. Stork, Peter E.Hart, 2015.
 A Course in Machine Learning by Hal Daumé III, 2017.
Dated
 Programming Collective Intelligence 《集体智慧编程》 2007 O'REILLY by Toby Segaran: Programming selected algorithms from scratch. Good to read when learning some ML courses (e.g. ML by Andrew Ng, Stanford).