A proven decision management methodology for increased profits and lowered risks Knowledge Automation: How to Implement Decision Management in Business Processes describes a simple but comprehensive methodology for decision management projects, which use business rules and predictive analytics to optimize and automate small, high-volume business decisions. It includes Decision Requirements Analysis (DRA), a new method for taking the crucial first step in any IT project to implement decision management: defining a set of business decisions and identifying all the information—business knowledge and data—required to make those decisions. Describes all the stages in automating business processes, from business process modeling down to the implementation of decision services Addresses how to use business rules and predictive analytics to optimize and automate small, high-volume business decisions Proposes a simple "top-down" method for defining decision requirements and representing them in a single diagram Shows how clear requirements can allow decision management projects to be run with reduced risk and increased profit Nontechnical and accessible, Knowledge Automation reveals how DRA is destined to become a standard technique in the business analysis and project management toolbox.

This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.

A Guide to the Automation Body of Knowledge provides you with comprehensive information about all major topics in the broad field of automation. Edited by Vernon Trevathan with contributions from over thirty leading experts from all aspects of automation, this book defines the most important automation concepts and processes, while also describing the technical skills professionals require to implement them in today's industrial environment. Whether you are an engineer, manager, control systems integrator, student, or educator, you will turn to this book again and again as the ultimate source on what is encompassed by automation.

Knowledge Café is a process for sharing information, whether face to face or virtual. This popular and practical knowledge management tool supports a culture where projects and innovation thrive. The Knowledge Café is a mindset and environment for engaging, discussing, and exchanging knowledge within a group either face to face or virtually. At the café, participants can discuss hard-to-solve project issues or resolve a family or community crisis. This metaphorical town square supports knowledge circulation and rejuvenation and increases its velocity—making it a breeding ground for innovation. The aha moments at one Knowledge Café can match the benefits of multiple conferences, workshops, and training put together. When knowledge management (KM) is part of an organization's culture, performance improves, collaboration increases, and the competitive advantage accelerates. No one can force knowledge transfer. We must create the right environment where knowledge is freely shared, rewarded, and fun. This book demonstrates why the Knowledge Café is such an effective KM tool and shows how to design optimal café experiences and increase learning agility. The premium on knowledge and agility has never been greater. This book offers a technique for managing knowledge toward the greater good. Tips; templates; practical and relatable experiences; case studies; and examples of knowledge brokers, creators, and sharers across cultures are sprinkled throughout the book to show how the café interfaces with other KM techniques and in different work and project spaces.

Like sysadmins before them, network engineers are finding that they cannot do their work manually anymore. As the field faces new protocols, technologies, delivery models, and a pressing need for businesses to be more agile and flexible, network automation is becoming essential. This practical guide shows network engineers how to use a range of technologies and tools—including Linux, Python, JSON, and XML—to automate their systems through code. Network programming and automation will help you simplify tasks involved in configuring, managing, and operating network equipment, topologies, services, and connectivity. Through the course of the book, you’ll learn the basic skills and tools you need to make this critical transition. This book covers: Python programming basics: data types, conditionals, loops, functions, classes, and modules Linux fundamentals to provide the foundation you need on your network automation journey Data formats and models: JSON, XML, YAML, and YANG for networking Jinja templating and its applicability for creating network device configurations The role of application programming interfaces (APIs) in network automation Source control with Git to manage code changes during the automation process How Ansible, Salt, and StackStorm open source automation tools can be used to automate network devices Key tools and technologies required for a Continuous Integration (CI) pipeline in network operations