We try to convey every idea necessary to reproduce the steps throughout this book. Nevertheless, there will be situations when you might get stuck. The reasons might range from simple typos over odd combinations of package versions to problems in understanding.
In such a situation, there are many different ways to get help. Most likely, your problem will already have been raised and solved in the following excellent Q&A sites:
#machinelearning
on Freenode – This IRC channel is focused on machine learning topics. It is a small but very active and helpful community of machine learning experts.As stated at the beginning, this book tries to help you get started quickly on your machine learning journey. We therefore highly encourage you to build up your own list of machine learning-related blogs and check them out regularly. This is the best way to get to know what works and what does not.
The only blog we want to highlight right here is http://blog.kaggle.com, the blog of the Kaggle company, which is carrying out machine learning competitions (more links are provided in Appendix A, Where to Learn More about Machine Learning). Typically, they encourage the winners of the competitions to write down how they approached the competition, what strategies did not work, and how they arrived at the winning strategy. If you don't read anything else, fine; but this is a must.