These three-volume book series cover a wide variety of topics in machine learning focusing on supervised and unsupervised learning, intended for data scientist and machine learning experts providing a very concise description of the scikit-learn library. The first volume covers the generalized linear models (linear & logistic regression).
General trace and log analysis patterns allow the application of uniform diagnostics and anomaly detection across diverse software environments. This pattern language covers any execution artifact from a small debugging trace to a distributed log with billions of messages from hundreds of computers, thousands of components, threads, and processes.