in such situationthere are many different ways to get help most likelyyour problem will already have been raised and solved in the following excellent & siteslearning topics for almost every questionit contains above-average answers from machine learning experts even if you don' have any questionsit is good habit to check it out every now and then and read through some of the questions and answers #machinelearning on freenode this irc channel is focused on machine learning topics it is small but very active and helpful community of machine learning experts is similar to metaoptimizedbut focuses more on statistics problems but with broader focus on general programming topics it containsfor examplemore questions on some of the packages that we will use in this book (scipy and matplotlibthe authorsto support you in topics that don' fit in any of the above buckets if you post your questionwe will get an instant messageif any of us are onlinewe will be drawn into chat with you as stated at the beginningthis 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 blog of the kaggle companywhich is carrying out machine learning competitions (more links are provided in appendixwhere to learn more about machine learningtypicallythey encourage the winners of the competitions to write down how they approached the competitionwhat strategies did not workand how they arrived at the winning strategy if you don' read anything elsefinebut this is must getting started assuming that you have already installed python (everything at least as recent as should be fine)we need to install numpy and scipy for numerical operations as well as matplotlib for visualization