| Year | Title | Info |
|---|---|---|
| 2022 | Geron: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow | The best book about data science and machine learning, perfect mixture of theory and practical coding examples |
| 2016 | Goodfellow: Deep Learning | The standard reference and bible of deep learning |
| 2015 | McDowell: Cracking the Coding Interview | Sets the standard for books of this kind |
| 2014 | Butcher: Seven Concurrency Models in Seven Weeks | Best overview and comparison of different concurrency models |
| 2013 | DeMarco: Peopleware: Productive Projects and Teams | Peopleware is the one book that everyone who runs a software team needs to read and reread once a year. |
| 2012 | Josuttis: The C++ Standard Library | The best book to start learning C++ |
| 2012 | White: Hadoop - The Definitive Guide | The bible of big data |
| 2011 | Krüger: Handbuch der Java-Programmierung | Best introduction to object oriented programming for Java in German |
| 2011 | Owen: Mahout in Action | Large scale machine learning |
| 2011 | Sedgewick: Algorithms | Best book on algorithms, because it shows real Java code, not just pseudocode |
| 2008 | Bloch: Effective Java (2nd Edition) | A senior Java developer must have read this book |
| 2008 | Martin: Clean Code | https://de.wikipedia.org/wiki/Clean_Code |
| 2007 | Bishop: Pattern Recognition and Machine Learning | Advanced bayesian perspective on classical machine learning |
| 2007 | Chapman: Fortran 95/2003 for Scientists and Engineers | Best book on modern Fortran |
| 2007 | Segaran: Programming Collective Intelligence | Perfect book about data mining and machine learning with Python |
| 2006 | Goetz: Java Concurrency in Practice | The reference about concurrent programming in Java |
| 2005 | Meyers: Effective C++ | Best book to improve your C++ |
| 1995 | Meyers: More Effective C++ | Second best book to improve your C++ |
| 1994 | Gamma: Design Patterns | https://en.wikipedia.org/wiki/Design_Patterns |
Other nice lists of links and books are: