[PDF] Data Science In Action - eBooks Review

Data Science In Action


Data Science In Action
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Process Mining


Process Mining
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Author : Wil M. P. van der Aalst
language : en
Publisher: Springer
Release Date : 2016-04-15

Process Mining written by Wil M. P. van der Aalst and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-15 with Computers categories.


This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.



Data Science In Action


Data Science In Action
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Author : Barrett Williams
language : en
Publisher: Barrett Williams
Release Date : 2025-07-09

Data Science In Action written by Barrett Williams and has been published by Barrett Williams this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-09 with Computers categories.


Unlock the transformative power of data with "Data Science in Action," your gateway to understanding how data science is revolutionizing diverse industries. This compelling eBook explores cutting-edge applications of data science that are not only reshaping businesses but also improving everyday lives. Dive into the world of healthcare, where data-driven insights are driving predictive analytics to prevent diseases and foster personalized medicine. Explore how retailers harness data to decipher consumer behavior and optimize pricing strategies, while financial institutions enhance risk management through sophisticated fraud detection and credit scoring models. "Data Science in Action" takes you beyond theory, presenting practical applications in marketing with targeted advertising and dynamic pricing strategies, and in education with adaptive learning systems that cater to individual needs. Discover the innovations transforming manufacturing processes through predictive maintenance and quality control, and see how smart farming techniques are boosting agricultural efficiency. From streamlining logistics in transportation to refining energy management with smart grids and renewable forecasts, every chapter unveils how data science is embedded in the fabric of our modern era. Uncover the secrets of viewer engagement in entertainment, and delve into data-driven decision-making in government policy and crime prevention. This book also ventures into real estate with predictive modeling and urban planning insights, unlocking the strategies behind successful property valuations. In sports, data is enhancing athlete performance and honing fan engagement strategies. "Data Science in Action" concludes with a forward-looking perspective on emerging trends and technologies, while addressing the ethical considerations and challenges inherent in this transformative field. Whether you're a data science enthusiast or a professional seeking to integrate data insights into your operations, this eBook is your ultimate guide to understanding and applying the principles of data science in practical, impactful ways. Transform how you perceive and utilize data today with "Data Science in Action."



Environmental Software Systems Data Science In Action


Environmental Software Systems Data Science In Action
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Author : Ioannis N. Athanasiadis
language : en
Publisher: Springer Nature
Release Date : 2020-01-29

Environmental Software Systems Data Science In Action written by Ioannis N. Athanasiadis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-29 with Computers categories.


This book constitutes the refereed proceedings of the 13th IFIP WG 5.11 International Symposium on Environmental Software Systems, ISESS 2020, held in Wageningen, The Netherlands, in February 2020. The 22 full papers and 3 short papers were carefully reviewed and selected from 29 submissions. The papers cover a wide range of topics on environmental informatics, including data mining, artificial intelligence, high performance and cloud computing, visualization and smart sensing for environmental, earth, agricultural and food applications.



Python Data Science Handbook


Python Data Science Handbook
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Author : Jake VanderPlas
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-11-21

Python Data Science Handbook written by Jake VanderPlas 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 2016-11-21 with Computers categories.


For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms



Data Science For Economics And Finance


Data Science For Economics And Finance
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Author : Sergio Consoli
language : en
Publisher: Springer Nature
Release Date : 2021-06-09

Data Science For Economics And Finance written by Sergio Consoli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-09 with Computers categories.


This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.



Data Science For Business


Data Science For Business
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Author : Foster Provost
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-07-27

Data Science For Business written by Foster Provost 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 2013-07-27 with Computers categories.


Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates



Process Mining In Action


Process Mining In Action
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Author : Lars Reinkemeyer
language : en
Publisher: Springer Nature
Release Date : 2020-03-14

Process Mining In Action written by Lars Reinkemeyer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-14 with Computers categories.


This book describes process mining use cases and business impact along the value chain, from corporate to local applications, representing the state of the art in domain know-how. Providing a set of industrial case studies and best practices, it complements academic publications on the topic. Further the book reveals the challenges and failures in order to offer readers practical insights and guidance on how to avoid the pitfalls and ensure successful operational deployment. The book is divided into three parts: Part I provides an introduction to the topic from fundamental principles to key success factors, and an overview of operational use cases. As a holistic description of process mining in a business environment, this part is particularly useful for readers not yet familiar with the topic. Part II presents detailed use cases written by contributors from a variety of functions and industries. Lastly, Part III provides a brief overview of the future of process mining, both from academic and operational perspectives. Based on a solid academic foundation, process mining has received increasing interest from operational businesses, with many companies already reaping the benefits. As the first book to present an overview of successful industrial applications, it is of particular interest to professionals who want to learn more about the possibilities and opportunities this new technology offers. It is also a valuable resource for researchers looking for empirical results when considering requirements for enhancements and further developments.



Science In Action


Science In Action
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Author : Bruno Latour
language : en
Publisher: Harvard University Press
Release Date : 1987

Science In Action written by Bruno Latour and has been published by Harvard University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with History categories.


From weaker to stronger rhetoric : literature - Laboratories - From weak points to strongholds : machines - Insiders out - From short to longer networks : tribunals of reason - Centres of calculation.



Foundations Of Data Science


Foundations Of Data Science
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Author : Avrim Blum
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-23

Foundations Of Data Science written by Avrim Blum and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-23 with Computers categories.


Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.