Statistics For Engineers And Scientists With Connect Access Card
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Statistics For Engineers And Scientists With Connect Access Card
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Author : William Navidi
language : en
Publisher: McGraw-Hill Science/Engineering/Math
Release Date : 2011-01-01
Statistics For Engineers And Scientists With Connect Access Card written by William Navidi and has been published by McGraw-Hill Science/Engineering/Math this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-01 with Technology & Engineering categories.
This item is a package containing Navidi Statistics for Engineers and Scientists 3e + Connect Access card to accompany Navidi Statistics for Engineers and Scientists. Statistics for Engineers and Scientists stands out for its crystal clear presentation of applied statistics. Suitable for a one or two semester course, the book takes a practical approach to methods of statistical modeling and data analysis that are most often used in scientific work. Statistics for Engineers and Scientists features a unique approach highlighted by an engaging writing style that explains difficult concepts clearly, along with the use of contemporary real world data sets to help motivate students and show direct connections to industry and research. While focusing on practical applications of statistics, the text makes extensive use of examples to motivate fundamental concepts and to develop intuition.
Package Statistics For Engineers And Scientists With 1 Semester Connect Access Card
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Author : William Navidi
language : en
Publisher: McGraw-Hill Education
Release Date : 2013-11-21
Package Statistics For Engineers And Scientists With 1 Semester Connect Access Card written by William Navidi and has been published by McGraw-Hill Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-21 with Technology & Engineering categories.
Oceanobs 19 An Ocean Of Opportunity Volume Iii
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Author : Tong Lee
language : en
Publisher: Frontiers Media SA
Release Date : 2020-12-31
Oceanobs 19 An Ocean Of Opportunity Volume Iii written by Tong Lee and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-31 with Science categories.
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Loose Leaf For Statistics For Engineers And Scientists With Connect Access Card
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Author : William Navidi
language : en
Publisher: McGraw-Hill Education
Release Date : 2013-12-12
Loose Leaf For Statistics For Engineers And Scientists With Connect Access Card written by William Navidi and has been published by McGraw-Hill Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-12 with Technology & Engineering categories.
Statistics for Engineers and Scientists stands out for its crystal clear presentation of applied statistics. Suitable for a one or two semester course, the book takes a practical approach to methods of statistical modeling and data analysis that are most often used in scientific work. Statistics for Engineers and Scientists features a unique approach highlighted by an engaging writing style that explains difficult concepts clearly, along with the use of contemporary real world data sets to help motivate students and show direct connections to industry and research. While focusing on practical applications of statistics, the text makes extensive use of examples to motivate fundamental concepts and to develop intuition. McGraw-Hill is proud to offer Connect with the fourth edition of Navidi's, "Statistics for Engineers and Scientists." This innovative and powerful system helps your students learn more efficiently and gives you the ability to customize your homework problems simply and easily. Track individual student performance - by question, assignment, or in relation to the class overall with detailed grade reports. ConnectPlus provides students with all the advantages of Connect, plus 24/7 access to an eBook. Navidi's" Statistics for Engineers and Scientists," fourth edition, includes the power of McGraw-Hill's "LearnSmart"--a proven adaptive learning system that helps students learn faster, study more efficiently, and retain more knowledge through a series of adaptive questions. This innovative study tool pinpoints concepts the student does not understand and maps out a personalized plan for success.
Knowledge Management In The Development Of Data Intensive Systems
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Author : Ivan Mistrik
language : en
Publisher: CRC Press
Release Date : 2021-06-15
Knowledge Management In The Development Of Data Intensive Systems written by Ivan Mistrik and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-15 with Computers categories.
Data-intensive systems are software applications that process and generate Big Data. Data-intensive systems support the use of large amounts of data strategically and efficiently to provide intelligence. For example, examining industrial sensor data or business process data can enhance production, guide proactive improvements of development processes, or optimize supply chain systems. Designing data-intensive software systems is difficult because distribution of knowledge across stakeholders creates a symmetry of ignorance, because a shared vision of the future requires the development of new knowledge that extends and synthesizes existing knowledge. Knowledge Management in the Development of Data-Intensive Systems addresses new challenges arising from knowledge management in the development of data-intensive software systems. These challenges concern requirements, architectural design, detailed design, implementation and maintenance. The book covers the current state and future directions of knowledge management in development of data-intensive software systems. The book features both academic and industrial contributions which discuss the role software engineering can play for addressing challenges that confront developing, maintaining and evolving systems;data-intensive software systems of cloud and mobile services; and the scalability requirements they imply. The book features software engineering approaches that can efficiently deal with data-intensive systems as well as applications and use cases benefiting from data-intensive systems. Providing a comprehensive reference on the notion of data-intensive systems from a technical and non-technical perspective, the book focuses uniquely on software engineering and knowledge management in the design and maintenance of data-intensive systems. The book covers constructing, deploying, and maintaining high quality software products and software engineering in and for dynamic and flexible environments. This book provides a holistic guide for those who need to understand the impact of variability on all aspects of the software life cycle. It leverages practical experience and evidence to look ahead at the challenges faced by organizations in a fast-moving world with increasingly fast-changing customer requirements and expectations.
Data Science
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Author : Yang Wang
language : en
Publisher: Springer Nature
Release Date : 2022-08-10
Data Science written by Yang Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-10 with Computers categories.
This two volume set (CCIS 1628 and 1629) constitutes the refereed proceedings of the 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022 held in Chengdu, China, in August, 2022. The 65 full papers and 26 short papers presented in these two volumes were carefully reviewed and selected from 261 submissions. The papers are organized in topical sections on: Big Data Management and Applications; Data Security and Privacy; Applications of Data Science; Infrastructure for Data Science; Education Track; Regulatory Technology in Finance.
Managing Cloud Native Data On Kubernetes
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Author : Jeff Carpenter
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-12-02
Managing Cloud Native Data On Kubernetes written by Jeff Carpenter and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-02 with Computers categories.
Is Kubernetes ready for stateful workloads? This open source system has become the primary platform for deploying and managing cloud native applications. But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging. If you want to avoid the inefficiencies and duplicative costs of having separate infrastructure for applications and data, this practical guide can help. Using Kubernetes as your platform, you'll learn open source technologies that are designed and built for the cloud. Authors Jeff Carpenter and Patrick McFadin provide case studies to help you explore new use cases and avoid the pitfalls others have faced. You’ll get an insider's view of what's coming from innovators who are creating next-generation architectures and infrastructure. With this book, you will: Learn how to use basic Kubernetes resources to compose data infrastructure Automate the deployment and operations of data infrastructure on Kubernetes using tools like Helm and operators Evaluate and select data infrastructure technologies for use in your applications Integrate data infrastructure technologies into your overall stack Explore emerging technologies that will enhance your Kubernetes-based applications in the future
Data Engineering Best Practices
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Author : Richard J. Schiller
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-10-11
Data Engineering Best Practices written by Richard J. Schiller and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-11 with Computers categories.
Explore modern data engineering techniques and best practices to build scalable, efficient, and future-proof data processing systems across cloud platforms Key Features Architect and engineer optimized data solutions in the cloud with best practices for performance and cost-effectiveness Explore design patterns and use cases to balance roles, technology choices, and processes for a future-proof design Learn from experts to avoid common pitfalls in data engineering projects Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionRevolutionize your approach to data processing in the fast-paced business landscape with this essential guide to data engineering. Discover the power of scalable, efficient, and secure data solutions through expert guidance on data engineering principles and techniques. Written by two industry experts with over 60 years of combined experience, it offers deep insights into best practices, architecture, agile processes, and cloud-based pipelines. You’ll start by defining the challenges data engineers face and understand how this agile and future-proof comprehensive data solution architecture addresses them. As you explore the extensive toolkit, mastering the capabilities of various instruments, you’ll gain the knowledge needed for independent research. Covering everything you need, right from data engineering fundamentals, the guide uses real-world examples to illustrate potential solutions. It elevates your skills to architect scalable data systems, implement agile development processes, and design cloud-based data pipelines. The book further equips you with the knowledge to harness serverless computing and microservices to build resilient data applications. By the end, you'll be armed with the expertise to design and deliver high-performance data engineering solutions that are not only robust, efficient, and secure but also future-ready.What you will learn Architect scalable data solutions within a well-architected framework Implement agile software development processes tailored to your organization's needs Design cloud-based data pipelines for analytics, machine learning, and AI-ready data products Optimize data engineering capabilities to ensure performance and long-term business value Apply best practices for data security, privacy, and compliance Harness serverless computing and microservices to build resilient, scalable, and trustworthy data pipelines Who this book is for If you are a data engineer, ETL developer, or big data engineer who wants to master the principles and techniques of data engineering, this book is for you. A basic understanding of data engineering concepts, ETL processes, and big data technologies is expected. This book is also for professionals who want to explore advanced data engineering practices, including scalable data solutions, agile software development, and cloud-based data processing pipelines.
Effective Data Science Infrastructure
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Author : Ville Tuulos
language : en
Publisher: Simon and Schuster
Release Date : 2022-08-16
Effective Data Science Infrastructure written by Ville Tuulos and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-16 with Computers categories.
Effective Data Science Infrastructure teaches you to build data pipelines and project workflows that will supercharge data scientists and their projects. Based on state-of-the-art tools and concepts that power data operations of Netflix, this book introduces a customizable cloud-based approach to model development and MLOps that you can easily adapt to your company's specific needs. As you roll out these practical processes, your teams will produce better and faster results when applying data science and machine learning to a wide array of business problems.
Perspectives On Data Science For Software Engineering
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Author : Tim Menzies
language : en
Publisher: Morgan Kaufmann
Release Date : 2016-07-14
Perspectives On Data Science For Software Engineering written by Tim Menzies and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-14 with Computers categories.
Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community's leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. - Presents the wisdom of community experts, derived from a summit on software analytics - Provides contributed chapters that share discrete ideas and technique from the trenches - Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data - Presented in clear chapters designed to be applicable across many domains