This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.
Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition-as well as some we don´t yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn the algorithms for the tasks automatically from data. As computing devices grow more ubiquitous, a larger part of our lives and work is recorded digitally, and as ´´Big Data´´ has gotten bigger, the theory of machine learning-the foundation of efforts to process that data into knowledge-has also advanced. In this book, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications.
As one of the most comprehensive machine learning texts around, this book does justice to the field´s incredible richness, but without losing sight of the unifying principles. Peter Flach´s clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.
Learning Processing, Second Edition, is a friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages. Requiring no previous experience, this book is for the true programming beginner. It teaches the basic building blocks of programming needed to create cutting-edge graphics applications including interactive art, live video processing, and data visualization. Step-by-step examples, thorough explanations, hands-on exercises, and sample code, supports your learning curve. A unique lab-style manual, the book gives graphic and web designers, artists, and illustrators of all stripes a jumpstart on working with the Processing programming environment by providing instruction on the basic principles of the language, followed by careful explanations of select advanced techniques. The book has been developed with a supportive learning experience at its core. From algorithms and data mining to rendering and debugging, it teaches object-oriented programming from the ground up within the fascinating context of interactive visual media. This book is ideal for graphic designers and visual artists without programming background who want to learn programming. It will also appeal to students taking college and graduate courses in interactive media or visual computing, and for self-study. A friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages No previous experience required-this book is for the true programming beginner! Step-by-step examples, thorough explanations, hands-on exercises, and sample code supports your learning curve
Gain hands-on experience with SPARQL, the RDF query language that?s bringing new possibilities to semantic web, linked data, and big data projects. This updated and expanded edition shows you how to use SPARQL 1.1 with a variety of tools to retrieve, manipulate, and federate data from the public web as well as from private sources. Author Bob DuCharme has you writing simple queries right away before providing background on how SPARQL fits into RDF technologies. Using short examples that you can run yourself with open source software, you?ll learn how to update, add to, and delete data in RDF datasets. * Get the big picture on RDF, linked data, and the semantic web * Use SPARQL to find bad data and create new data from existing data * Use datatype metadata and functions in your queries * Learn techniques and tools to help your queries run more efficiently * Use RDF Schemas and OWL ontologies to extend the power of your queries * Discover the roles that SPARQL can play in your applications
Learning Agile is a comprehensive guide to the most popular agile methods, written in a light and engaging style that makes it easy for you to learn. Agile has revolutionized the way teams approach software development, but with dozens of agile methodologies to choose from, the decision to ´´go agile´´ can be tricky. This practical book helps you sort it out, first by grounding you in agile?s underlying principles, then by describing four specific?and well-used?agile methods: Scrum, extreme programming (XP), Lean, and Kanban. Each method focuses on a different area of development, but they all aim to change your team?s mindset?from individuals who simply follow a plan to a cohesive group that makes decisions together. Whether you?re considering agile for the first time, or trying it again, you?ll learn how to choose a method that best fits your team and your company. * Understand the purpose behind agile?s core values and principles * Learn Scrum?s emphasis on project management, self-organization, and collective commitment * Focus on software design and architecture with XP practices such as test-first and pair programming * Use Lean thinking to empower your team, eliminate waste, and deliver software fast * Learn how Kanban?s practices help you deliver great software by managing flow * Adopt agile practices and principles with an agile coach
Get a hands-on introduction to the Chef, the configuration management tool for solving operations issues in enterprises large and small. Ideal for developers and sysadmins new to configuration management, this guide shows you to automate the packaging and delivery of applications in your infrastructure. You?ll be able to build (or rebuild) your infrastructure?s application stack in minutes or hours, rather than days or weeks. After teaching you how to write Ruby-based Chef code, this book walks you through different Chef tools and configuration management concepts in each chapter, using detailed examples throughout. All you need to get started is command-line experience and familiarity with basic system administration. * Configure your Chef development environment and start writing recipes * Create Chef cookbooks with recipes for each part of your infrastructure * Use Test Kitchen to manage sandbox testing environments * Manage single nodes with Chef client, and multiple nodes with Chef Server * Use data bags for storing shared global data between nodes * Simulate production Chef Server environments with Chef Zero * Classify different types of services in your infrastructure with roles * Model life stages of your application, including development, testing, staging, and production