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Hands-On Data Analysis in R for Finance
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Hands-On Data Analysis in R for FinanceНазвание: Hands-On Data Analysis in R for Finance
Автор: Jean-Francois Collard
Издательство: CRC Press
Год: 2023
Страниц: 414
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

The subject of this textbook is to act as an introduction to data science/data analysis applied to finance, using R and its most recent and freely available extension libraries. The targeted academic level is undergrad students with a major in data science and/or finance and graduate students, and of course practitioners/professionals who need a desk reference. Assumes no prior knowledge of R; The content has been tested in actual university classes; Makes the reader proficient in advanced methods such as machine learning, time series analysis, principal component analysis and more; Gives comprehensive and detailed explanations on how to use the most recent and free resources, such as financial and statistics libraries or open database on the internet.


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Data Science and Analytics for SMEs: Consulting, Tools , Practical Use Cases
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Data Science and Analytics for SMEs: Consulting, Tools , Practical Use CasesНазвание: Data Science and Analytics for SMEs: Consulting, Tools , Practical Use Cases
Автор: Afolabi Ibukun Tolulope
Издательство: Apress
Год: 2022
Страниц: 341
Язык: английский
Формат: pdf (true), epub
Размер: 10.6 MB, 23.3 MB

Master the tricks and techniques of business analytics consulting, specifically applicable to small-to-medium businesses (SMEs). Written to help you hone your business analytics skills, this book applies data science techniques to help solve problems and improve upon many aspects of a business' operations. In simple terms, Data Science refers to the ability to take data, generate an understanding from the data, process the data, extract value from the data, visualize the data, and present it in such a way that decisions can be made from this presentation. Data science is described as the process of extracting knowledge from huge amounts of data. It is an intersection of Mathematics, Statistics, Visualization, and Artificial Intelligence. Artificial Intelligence (AI) is a superset of machine learning, which is a superset of Deep Learning (DL).


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Data Science in Context: Foundations, Challenges, Opportunities
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Data Science in Context: Foundations, Challenges, OpportunitiesНазвание: Data Science in Context: Foundations, Challenges, Opportunities
Автор: Alfred Z. Spector, Peter Norvig
Издательство: Cambridge University Press
Год: 2023
Страниц: 333
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Data Science is the foundation of our modern world. It underlies applications used by billions of people every day, providing new tools, forms of entertainment, economic growth, and potential solutions to difficult, complex problems. These opportunities come with significant societal consequences, raising fundamental questions about issues such as data quality, fairness, privacy, and causation. In this book, four leading experts convey the excitement and promise of Data Science and examine the major challenges in gaining its benefits and mitigating its harms. Some of Data Science’s most important techniques emerged from work across disciplines. While we include machine learning within computing, its development included contributions from statistics, pattern recognition, and neuropsychology. Information visualization arose from statistics, but has benefited greatly from computing’s contributions.


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Handbook for SAP PP in S/4HANA: Production Planning and Execution in SAP S/4HANA
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Название: Handbook for SAP PP in S/4HANA: Production Planning and Execution in SAP S/4HANA
Автор: Himanshu Goel
Издательство: Apress
Год: 2022
Формат: True PDF
Страниц: 477
Размер: 25,8 Mb
Язык: English

Author Himanshu Goel begins by explaining the nuts and bolts of production planning in SAP S/4HANA, before delving into various manufacturing methodologies such as discrete manufacturing, repetitive manufacturing, and process industry. He'll then walk you through setting up master data such as the material master, bill of material, work center, routing, and production version. You'll then learn, step-by-step, how SAP PP processes are established from production order-based manufacturing to process order-based manufacturing.


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The IoT Product Manager: A Handbook for Engineers, Data Analysts, and Other IT Professionals
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Название: The IoT Product Manager: A Handbook for Engineers, Data Analysts, and Other IT Professionals
Автор: Padmaraj Nidagundi
Издательство: Apress
Год: 2022
Формат: True PDF
Страниц: 207
Размер: 10 Mb
Язык: English

Enhance your product management skills and set yourself apart from other product managers working in the IoT industry. This book shows you how to navigate through the world of small and Edge devices to successfully launch and monitor products connected together to make smart environments.


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Troubleshooting Microsoft Teams: Enlisting the Right Approach and Tools in Teams for Mapping and Troubleshooting Issues
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Название: Troubleshooting Microsoft Teams: Enlisting the Right Approach and Tools in Teams for Mapping and Troubleshooting Issues
Автор: Balu N Ilag, Arun M Sabale
Издательство: Apress
Год: 2022
Формат: True PDF
Страниц: 481
Размер: 22,7 Mb
Язык: English

Learn and understand Microsoft Teams functionality, potential issues, and the tools available to troubleshoot Teams. This book provides a complete overview of Teams Phone system (PSTN) connectivity, call routing and quality troubleshooting, and best practices to support a Teams environment.


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IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, 17th Edition
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IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, 17th EditionНазвание: IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, 17th Edition
Автор: Darren George, Paul Mallery
Издательство: Routledge
Год: 2022
Страниц: 419
Язык: английский
Формат: pdf (true)
Размер: 16.6 MB

IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, seventeenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike. Extensive use of four-color screen shots, clear writing, and step-by-step boxes guide readers through the program. Output for each procedure is explained and illustrated, and every output term is defined. Exercises at the end of each chapter support students by providing additional opportunities to practice using SPSS. IBM SPSS Statistics Software (“SPSS”) is a powerful tool that is capable of conducting just about any type of data analysis used in the social sciences, the natural sciences, or in the business world. Mathematics is the language of science, and data analysis is the dialect of research. The present book is designed to make data analysis more comprehensible and less toxic.


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Enterprise Systems Architecture: Aligning Business Operating Models to Technology Landscapes
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Enterprise Systems Architecture: Aligning Business Operating Models to Technology LandscapesНазвание: Enterprise Systems Architecture: Aligning Business Operating Models to Technology Landscapes
Автор: Daljit Roy Banger
Издательство: Apress
Год: 2022
Страниц: 306
Язык: английский
Формат: pdf, epub
Размер: 17.0 MB

Enhance your technical and business skills to better manage your organization’s technology ecosystem. This book aims to explain how to align the technology landscape to service your company’s business operating model. The book begins by exploring different architectural approaches before taking a deep dive into multiple layers of the architectural stack and the methodology of each component. You’ll also learn about the many products delivered by enterprise architecture. To complete the book, author Daljit Banger delves into the various roles and responsibilities of an enterprise architect.


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Locating Eigenvalues in Graphs: Algorithms and Applications
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Locating Eigenvalues in Graphs: Algorithms and ApplicationsНазвание: Locating Eigenvalues in Graphs: Algorithms and Applications
Автор: Carlos Hoppen, David P. Jacobs, Vilmar Trevisan
Издательство: Springer
Год: 2022
Страниц: 142
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB

This book focuses on linear time eigenvalue location algorithms for graphs. This subject relates to spectral graph theory, a field that combines tools and concepts of linear algebra and combinatorics, with applications ranging from image processing and data analysis to molecular descriptors and random walks. It has attracted a lot of attention and has since emerged as an area on its own. Perhaps surprisingly, eigenvalues and eigenvectors turn out to be intimately connected with the structure of a graph. In terms of applications, they have proved to be useful for isomorphism testing and embedding graphs in the plane, for graph partitioning and clustering, as topological descriptors for networks and molecules, in the geometric description of data sets in Data Science, and in the design of efficient networks, just to mention a few. In this book, we survey the evolution of eigenvalue location algorithms in an organized and unified way, starting with algorithms for trees and other well-known graph classes, such as cographs, and showing how they motivated more recent algorithms that may be applied to arbitrary graphs, but whose efficiency depends on the existence of a graph decomposition of low complexity. While they are vastly deeper than the simple tree algorithm, we wish to convince the readers that they are similar in spirit.


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Demystifying Graph Data Science: Graph algorithms, analytics methods, platforms, databases, and use cases
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Demystifying Graph Data Science: Graph algorithms, analytics methods, platforms, databases, and use casesНазвание: Demystifying Graph Data Science: Graph algorithms, analytics methods, platforms, databases, and use cases
Автор: Pethuru Raj, Abhishek Kumar, Vicente García Díaz
Издательство: The Institution of Engineering and Technology
Год: 2022
Страниц: 415
Язык: английский
Формат: pdf (true), epub
Размер: 32.8 MB

With the growing maturity and stability of digitization and edge technologies, vast numbers of digital entities, connected devices, and microservices interact purposefully to create huge sets of poly-structured digital data. Corporations are continuously seeking fresh ways to use their data to drive business innovations and disruptions to bring in real digital transformation. Data Science (DS) is proving to be the one-stop solution for simplifying the process of knowledge discovery and dissemination out of massive amounts of multi-structured data. Supported by query languages, databases, algorithms, platforms, analytics methods and Machine and Deep Learning (ML and DL) algorithms, graphs are now emerging as a new data structure for optimally representing a variety of data and their intimate relationships.