Some interesting and freely available books, which can be found at their respective authors websites:
Title  Language  Link  

1  An Introduction to Statistical Learning with Applications in R (2nd Ed.)  English  Link (Homepage) 
2  The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd Ed.)  English  Link (Homepage) 
3  Mathematics for Machine Learning  English  Link (Homepage) 
4  Foundations of Machine Learning (2nd Ed.)  English  Link (Homepage) 
5  Pattern Recognition and Machine Learning  English  Link (Homepage) 
6  Reinforcement Learning: An Introduction  English  Link (Homepage) 
7  Deep Learning  English  Homepage 
8  Dive into Deep Learning  English  Homepage (New version) 
A highbias, lowvariance introduction to Machine Learning for physicists  English  arXiv.org  
Speech and Language Processing  English  Link  
Understanding Machine Learning: From Theory to Algorithms  English  Homepage  
Bayesian Reasoning and Machine Learning  English  Homepage 
Some additional interesting reading
Title  Link  

"Apparently, Calculus Was Invented In 1994"  [1], [2]  
"Oh No! I Got the Wrong Sign! What Should I Do?"  [2002], [2005]  
"I Just Ran Two Million Regressions"  Link  
"Biased versus unbiased estimation"  Link  
"The significance of significance"  Link, [1], [2]  
"On the Significance of Significance: Addressing a Basic Problem in Research"  Link (needs university VPN)  
"Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations"  Link  
Machine Learning: An Applied Econometric Approach  Link  
"The Gaussian Copula and the Financial Crisis" and possible problems in the future  [1], [2], [3] + [4] 

Buggy Software  [1], [2] 

R Development NEWS:  Link  
Python Release Schedules:  [3.10] + [Index of Python Enhancement Proposals] 
Python: handcalcs (render Python calculation code automatically in LaTeX)
C/C++ :
Various types of charts/plots with explanations: The Data Visualisation Catalogue