Showing results for "michael kaufmann"
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GitHub Actions Cookbook
A practical guide to automating repetitive tasks and streamlining your development process
2024
EN
Authored by a Microsoft Regional Director, this book shows you how to leverage the power of the community-driven GitHub Actions workflow platform to automate repetitive engineering tasksKey FeaturesAutomate CI/CD workflows and deploy securely to cloud providers like Azure, AWS, or GCP using OpenIDCreate your own custom actions with Docker, JavaScript programming, or shell scripts and share them with othersDiscover ways to automate complex scena...
Accelerate DevOps with GitHub
Enhance software delivery performance with GitHub Issues, Projects, Actions, and Advanced Security
2022
EN
Take your DevOps and DevSecOps game to the next level by leveraging the power of the GitHub toolset in practiceKey FeaturesRelease software faster and with confidenceIncrease your productivity by spending more time on software delivery and less on fixing bugs and administrative tasksDeliver high-quality software that is more stable, scalable, and secureBook DescriptionThis practical guide to DevOps uses GitHub as the DevOps p...
GitHub Actions in Action
Continuous integration and delivery for DevOps
2025
EN
Automate your build, test, and deploy pipelines using GitHub Actions!Continuous delivery (CI/CD) pipelines help you automate the software development process and maximize your team’s efficiency. GitHub Actions in Action teaches you how to build, test, and deploy pipelines in GitHub Actions through hands-on labs and projects.In GitHub Actions in Action you will learn how to:Create and share GitHub Actions workflowsAu...
SQL and NoSQL Databases
Modeling, Languages, Security and Architectures for Big Data Management
2023
EN
This textbook offers a comprehensive introduction to relational (SQL) and non-relational (NoSQL) databases. The authors thoroughly review the current state of database tools and techniques and examine upcoming innovations.In the first five chapters, the authors analyze in detail the management, modeling, languages, security, and architecture of relational databases, graph databases, and document databases. Moreover, an overview of other SQL- and NoSQL-based database approaches is p...
SQL & NoSQL Databases
Models, Languages, Consistency Options and Architectures for Big Data Management
2019
EN
This book offers a comprehensive introduction to relational (SQL) and non-relational (NoSQL) databases. The authors thoroughly review the current state of database tools and techniques, and examine coming innovations.The book opens with a broad look at data management, including an overview of information systems and databases, and an explanation of contemporary database types:SQL and NoSQL databases, and their respective management systemsThe n...
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- Business and Management (R0)
2014
EN
To enhance marketing analytics, approximate and inductive reasoning can be applied to handle uncertainty in individual marketing models. This book demonstrates the use of fuzzy logic for classification and segmentation in marketing campaigns. Based on practical experience as a data analyst and on theoretical studies as a researcher, the author explains fuzzy classification, inductive logic and the concept of likelihood and introduces a blend of Bayesian and Fuzzy Set approaches, allowing r...
Graph-Theoretic Concepts in Computer Science
48th International Workshop, WG 2022, Tübingen, Germany, June 22–24, 2022, Revised Selected Papers
2022
EN
This LNCS 13453 constitutes the thoroughly refereed proceedings of the 48th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2022.The 32 full papers presented in this volume were carefully reviewed and selected from a total of 96 submissions. The WG 2022 workshop aims to merge theory and practice by demonstrating how concepts from Graph Theory can be applied to various areas in Computer Science, or by extracting new graph theoretic problems from applications.
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2008
EN
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using...
Data Analysis and Data Mining
An Introduction
2012
EN
An introduction to statistical data mining, Data Analysis and Data Mining is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical models to students and professional statisticians-both those working in communications and those working in a technological or scientific capacity-who have a limited knowledge of data mining. This book presents key statistical concepts by w...
Causal Inference in Statistics
A Primer
2016
EN
CAUSAL INFERENCE IN STATISTICSA PrimerCausality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can...
2016
EN
Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling and system design. This comprehensive treatment of the statistical issues ...
Mastering Predictive Analytics with R
Master the craft of predictive modeling by developing strategy, intuition, and a solid foundation in essential concepts
2015
EN
Key FeaturesBook DescriptionThis book is intended for the budding data scientist, predictive modeler, or quantitative analyst with only a basic exposure to R and statistics. It is also designed to be a reference for experienced professionals wanting to brush up on the details of a particular type of predictive model. Mastering Predictive Analytics with R assumes familiarity with only the fundamentals of R, such as the main data types, simple functions,...











