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Data Science with Raspberry Pi
by G. Anand K. Mohaideen Abdul KadharImplement real-time data processing applications on the Raspberry Pi. This book uniquely helps you work with data science concepts as part of real-time applications using the Raspberry Pi as a localized cloud. <P><P> You’ll start with a brief introduction to data science followed by a dedicated look at the fundamental concepts of Python programming. Here you’ll install the software needed for Python programming on the Pi, and then review the various data types and modules available. The next steps are to set up your Pis for gathering real-time data and incorporate the basic operations of data science related to real-time applications. You’ll then combine all these new skills to work with machine learning concepts that will enable your Raspberry Pi to learn from the data it gathers. Case studies round out the book to give you an idea of the range of domains where these concepts can be applied. <P><P> By the end of Data Science with the Raspberry Pi, you’ll understand that many applications are now dependent upon cloud computing. As Raspberry Pis are cheap, it is easy to use a number of them closer to the sensors gathering the data and restrict the analytics closer to the edge. You’ll find that not only is the Pi an easy entry point to data science, it also provides an elegant solution to cloud computing limitations through localized deployment.
Data Science with SQL Server Quick Start Guide: Integrate SQL Server with data science
by Dejan SarkaGet unique insights from your data by combining the power of SQL Server, R and PythonKey FeaturesUse the features of SQL Server 2017 to implement the data science project life cycleLeverage the power of R and Python to design and develop efficient data modelsfind unique insights from your data with powerful techniques for data preprocessing and analysisBook DescriptionSQL Server only started to fully support data science with its two most recent editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning (ML) Services for your projects, then this is the ideal book for you.This book is the ideal introduction to data science with Microsoft SQL Server and In-Database ML Services. It covers all stages of a data science project, from businessand data understanding,through data overview, data preparation, modeling and using algorithms, model evaluation, and deployment.You will learn to use the engines and languages that come with SQL Server, including ML Services with R and Python languages and Transact-SQL. You will also learn how to choose which algorithm to use for which task, and learn the working of each algorithm.What you will learnUse the popular programming languages,T-SQL, R, and Python, for data scienceUnderstand your data with queries and introductory statisticsCreate and enhance the datasets for MLVisualize and analyze data using basic and advanced graphsExplore ML using unsupervised and supervised modelsDeploy models in SQL Server and perform predictionsWho this book is forSQL Server professionals who want to start with data science, and data scientists who would like to start using SQL Server in their projects will find this book to be useful. Prior exposure to SQL Server will be helpful.
Data Science with Semantic Technologies: Deployment and Exploration
by Narayan C. Debnath Archana PatelGone are the days when data was interlinked with related data by humans and human interpretation was required. Data is no longer just data. It is now considered a Thing or Entity or Concept with meaning, so that a machine not only understands the concept but also extrapolates the way humans do.Data Science with Semantic Technologies: Deployment and Exploration, the second volume of a two-volume handbook set, provides a roadmap for the deployment of semantic technologies in the field of data science and enables the user to create intelligence through these technologies by exploring the opportunities and eradicating the challenges in the current and future time frame. In addition, this book offers the answer to various questions like: What makes a technology semantic as opposed to other approaches to data science? What is knowledge data science? How does knowledge data science relate to other fields? This book explores the optimal use of these technologies to provide the highest benefit to the user under one comprehensive source and title. As there is no dedicated book available in the market on this topic at this time, this book becomes a unique resource for scholars, researchers, data scientists, professionals, and practitioners. This volume can serve as an important guide toward applications of data science with semantic technologies for the upcoming generation.
Data Science with Semantic Technologies: Theory, Practice and Application (Advances in Intelligent and Scientific Computing)
by Narayan C. Debnath Bharat Bhusan Archana PatelDATA SCIENCE WITH SEMANTIC TECHNOLOGIES This book will serve as an important guide toward applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for scholars, researchers, professionals, and practitioners in this field. To create intelligence in data science, it becomes necessary to utilize semantic technologies which allow machine-readable representation of data. This intelligence uniquely identifies and connects data with common business terms, and it also enables users to communicate with data. Instead of structuring the data, semantic technologies help users to understand the meaning of the data by using the concepts of semantics, ontology, OWL, linked data, and knowledge-graphs. These technologies help organizations to understand all the stored data, adding the value in it, and enabling insights that were not available before. As data is the most important asset for any organization, it is essential to apply semantic technologies in data science to fulfill the need of any organization. Data Science with Semantic Technologies provides a roadmap for the deployment of semantic technologies in the field of data science. Moreover, it highlights how data science enables the user to create intelligence through these technologies by exploring the opportunities and eradicating the challenges in the current and future time frame. In addition, this book provides answers to various questions like: Can semantic technologies be able to facilitate data science? Which type of data science problems can be tackled by semantic technologies? How can data scientists benefit from these technologies? What is knowledge data science? How does knowledge data science relate to other domains? What is the role of semantic technologies in data science? What is the current progress and future of data science with semantic technologies? Which types of problems require the immediate attention of researchers? Audience Researchers in the fields of data science, semantic technologies, artificial intelligence, big data, and other related domains, as well as industry professionals, software engineers/scientists, and project managers who are developing the software for data science. Students across the globe will get the basic and advanced knowledge on the current state and potential future of data science.
Data Science – was ist das eigentlich?!: Algorithmen des maschinellen Lernens verständlich erklärt
by Annalyn Ng Kenneth SooSie möchten endlich wissen, was sich hinter Schlagworten wie „Data Science“ und „Machine Learning“ eigentlich verbirgt – und was man alles damit anstellen kann? Auf allzu viel Mathematik würden Sie dabei aber gern verzichten? Dann sind Sie hier genau richtig: Dieses Buch bietet einen kompakten Einblick in die wichtigsten Schlüsselkonzepte der Datenwissenschaft und ihrer Algorithmen – und zwar ohne Sie mit mathematischen Formeln und Details zu belasten! Der Fokus liegt – nach einer übergeordneten Einführung – auf Anwendungen des maschinellen Lernens zur Mustererkennung und Vorhersage von Ergebnissen: In jedem Kapitel wird ein Algorithmus erläutert und mit einem leicht verständlichen, realen Anwendungsbeispiel verknüpft. Die Kombination aus intuitiven Erklärungen und zahlreichen Abbildungen ermöglicht dabei ein grundlegendes Verständnis, das ohne mathematische Formelsprache auskommt. Abschließend werden auch die Grenzen und Nachteile der betrachteten Algorithmen explizit aufgezeigt.
Data Science, Learning by Latent Structures, and Knowledge Discovery (Studies in Classification, Data Analysis, and Knowledge Organization)
by Berthold Lausen Sabine Krolak-Schwerdt Matthias BöhmerThis volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering and pattern recognition methods; strategies for modeling complex data and mining large data sets; applications of advanced methods in specific domains of practice. The contributions offer interesting applications to various disciplines such as psychology, biology, medical and health sciences; economics, marketing, banking and finance; engineering; geography and geology; archeology, sociology, educational sciences, linguistics and musicology; library science. The book contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French-speaking Classification Society (SFC) in July 2013 at the University of Luxembourg.
Data Science-Based Full-Lifespan Management of Lithium-Ion Battery: Manufacturing, Operation and Reutilization (Green Energy and Technology)
by Xin Lai Kailong Liu Yujie WangThis open access book comprehensively consolidates studies in the rapidly emerging field of battery management. The primary focus is to overview the new and emerging data science technologies for full-lifespan management of Li-ion batteries, which are categorized into three groups, namely (i) battery manufacturing management, (ii) battery operation management, and (iii) battery reutilization management. The key challenges, future trends as well as promising data-science technologies to further improve this research field are discussed. As battery full-lifespan (manufacturing, operation, and reutilization) management is a hot research topic in both energy and AI fields and none specific book has focused on systematically describing this particular from a data science perspective before, this book can attract the attention of academics, scientists, engineers, and practitioners. It is useful as a reference book for students and graduates working in related fields. Specifically, the audience could not only get the basics of battery manufacturing, operation, and reutilization but also the information of related data-science technologies. The step-by-step guidance, comprehensive introduction, and case studies to the topic make it accessible to audiences of different levels, from graduates to experienced engineers.
Data Science: 10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024, Macao, China, September 27–30, 2024, Proceedings, Part I (Communications in Computer and Information Science #2213)
by Qilong Han Xianhua Song Zeguang Lu Chen Yu Jianping Wang Chengzhong Xu Haiwei PanThis three-volume set CCIS 2213-2215 constitutes the refereed proceedings of the 10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024, held in Macau, China, during September 27–30, 2024. The 74 full papers and 3 short papers presented in these three volumes were carefully reviewed and selected from 249 submissions. The papers are organized in the following topical sections: Part I: Novel methods or tools used in big data and its applications; applications of data science. Part II: Education research, methods and materials for data science and engine; data security and privacy; big data mining and knowledge management. Part III: Infrastructure for data science; social media and recommendation system; multimedia data management and analysis.
Data Science: 10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024, Macao, China, September 27–30, 2024, Proceedings, Part II (Communications in Computer and Information Science #2214)
by Qilong Han Xianhua Song Zeguang Lu Chen Yu Jianping Wang Chengzhong Xu Haiwei PanThis three-volume set CCIS 2213-2215 constitutes the refereed proceedings of the 10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024, held in Macau, China, during September 27–30, 2024. The 74 full papers and 3 short papers presented in these three volumes were carefully reviewed and selected from 249 submissions. The papers are organized in the following topical sections: Part I: Novel methods or tools used in big data and its applications; applications of data science. Part II: Education research, methods and materials for data science and engine; data security and privacy; big data mining and knowledge management. Part III: Infrastructure for data science; social media and recommendation system; multimedia data management and analysis.
Data Science: 10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024, Macao, China, September 27–30, 2024, Proceedings, Part III (Communications in Computer and Information Science #2215)
by Qilong Han Xianhua Song Zeguang Lu Chen Yu Jianping Wang Chengzhong Xu Haiwei PanThis three-volume set CCIS 2213-2215 constitutes the refereed proceedings of the 10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024, held in Macau, China, during September 27–30, 2024. The 74 full papers and 3 short papers presented in these three volumes were carefully reviewed and selected from 249 submissions. The papers are organized in the following topical sections: Part I: Novel methods or tools used in big data and its applications; applications of data science. Part II: Education research, methods and materials for data science and engine; data security and privacy; big data mining and knowledge management. Part III: Infrastructure for data science; social media and recommendation system; multimedia data management and analysis.
Data Science: 20th International Conference, ICDATA 2024, Held as Part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024, Las Vegas, NV, USA, July 22–25, 2024, Revised Selected Papers (Communications in Computer and Information Science #2253)
by Hamid R. Arabnia Robert StahlbockThis book constitutes the proceedings of the 20th International Conference on Data Science, ICDATA 2024, held as part of the 2024 World Congress in Computer Science, Computer Engineering and Applied Computing, in Las Vegas, USA, during July 22 to July 25, 2024. This proceedings book includes 39 papers selected from a total of 243 submissions. They are organized in topical sections as follows: Artificial intelligence, data science, and neural networks; natural language processing, large language modelc, generative AI; data science, data analytics, and applications; prediction and forecasting and security applications; and poster papers.
Data Science: 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, Sydney, NSW, Australia, June 10-13, 2025, Proceedings, Part VI (Lecture Notes in Computer Science #15875)
by Longbing Cao Myra Spiliopoulou Vipin Kumar Can Wang Joao Gama Xintao Wu Xiangmin Zhou Guansong PangThe two-volume set LNAI 15875 + 15876 constitutes the proceedings of the 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025 Special Session, held in Sydney, NSW, Australia, during June 10–13, 2025. The 68 full papers included in this set were carefully reviewed and selected from 696 submissions. They were organized in topical sections as follows: survey track; machine learning; trustworthiness; learning on complex data; graph mining; machine learning applications; representation learning; scientific/business data analysis; and special track on large language models.
Data Science: 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, Sydney, NSW, Australia, June 10-13, 2025, Proceedings, Part VII (Lecture Notes in Computer Science #15876)
by Longbing Cao Myra Spiliopoulou Vipin Kumar Can Wang Joao Gama Xintao Wu Xiangmin Zhou Guansong PangThe two-volume set LNAI 15875 + 15876 constitutes the proceedings of the 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025 Special Session, held in Sydney, NSW, Australia, during June 10–13, 2025. The 68 full papers included in this set were carefully reviewed and selected from 696 submissions. They were organized in topical sections as follows: survey track; machine learning; trustworthiness; learning on complex data; graph mining; machine learning applications; representation learning; scientific/business data analysis; and special track on large language models.
Data Science: 30th British International Conference on Databases, BICOD 2015, Edinburgh, UK, July 6-8, 2015, Proceedings (Lecture Notes in Computer Science #9147)
by Sebastian ManethThis book constitutes the refereed conference proceedings of the 30th British International Conference on Databases, BICOD 2015 - formerly known as BNCOD (British National Conference on Databases) - held in Edinburgh, UK, in July 2015. The 19 revised full papers, presented together with three invited keynotes and three invited lectures were carefully reviewed and selected from 37 submissions. Special focus of the conference has been "Data Science" and so the papers cover a wide range of topics related to databases and data-centric computation.
Data Science: 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018, Zhengzhou, China, September 21-23, 2018, Proceedings, Part I (Communications in Computer and Information Science #901)
by Yan Wang Weipeng Jing Xianhua Song Zeguang Lu Yong Gan Qinglei ZhouThis two volume set (CCIS 901 and 902) constitutes the refereed proceedings of the 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018 (originally ICYCSEE) held in Zhengzhou, China, in September 2018. The 125 revised full papers presented in these two volumes were carefully reviewed and selected from 1057 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including mathematical issues in data science, computational theory for data science, big data management and applications, data quality and data preparation, evaluation and measurement in data science, data visualization, big data mining and knowledge management, infrastructure for data science, machine learning for data science, data security and privacy, applications of data science, case study of data science, multimedia data management and analysis, data-driven scientific research, data-driven bioinformatics, data-driven healthcare, data-driven management, data-driven eGovernment, data-driven smart city/planet, data marketing and economics, social media and recommendation systems, data-driven security, data-driven business model innovation, social and/or organizational impacts of data science.
Data Science: 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018, Zhengzhou, China, September 21-23, 2018, Proceedings, Part II (Communications in Computer and Information Science #902)
by Yan Wang Hongzhi Wang Zeguang Lu Wei Xie Qinglei Zhou Qiguang MiaoThis two volume set (CCIS 901 and 902) constitutes the refereed proceedings of the 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018 (originally ICYCSEE) held in Zhengzhou, China, in September 2018. The 125 revised full papers presented in these two volumes were carefully reviewed and selected from 1057 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including mathematical issues in data science, computational theory for data science, big data management and applications, data quality and data preparation, evaluation and measurement in data science, data visualization, big data mining and knowledge management, infrastructure for data science, machine learning for data science, data security and privacy, applications of data science, case study of data science, multimedia data management and analysis, data-driven scientific research, data-driven bioinformatics, data-driven healthcare, data-driven management, data-driven eGovernment, data-driven smart city/planet, data marketing and economics, social media and recommendation systems, data-driven security, data-driven business model innovation, social and/or organizational impacts of data science.
Data Science: 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019, Guilin, China, September 20–23, 2019, Proceedings, Part I (Communications in Computer and Information Science #1058)
by Weipeng Jing Xianhua Song Zeguang Lu Xiaohui ChengThis two volume set (CCIS 1058 and 1059) constitutes the refereed proceedings of the 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019 held in Guilin, China, in September 2019. The 104 revised full papers presented in these two volumes were carefully reviewed and selected from 395 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including data mining; data base; net work; security; machine learning; bioinformatics; natural language processing; software engineering; graphic images; system; education; application.
Data Science: 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019, Guilin, China, September 20–23, 2019, Proceedings, Part II (Communications in Computer and Information Science #1059)
by Hongzhi Wang Zeguang Lu Xiaolan Xie Rui MaoThis two volume set (CCIS 1058 and 1059) constitutes the refereed proceedings of the 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019 held in Guilin, China, in September 2019. The 104 revised full papers presented in these two volumes were carefully reviewed and selected from 395 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including data mining; data base; net work; security; machine learning; bioinformatics; natural language processing; software engineering; graphic images; system; education; application.
Data Science: 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020, Taiyuan, China, September 18-21, 2020, Proceedings, Part I (Communications in Computer and Information Science #1257)
by Weipeng Jing Xianhua Song Zeguang Lu Jianchao ZengThis two volume set (CCIS 1257 and 1258) constitutes the refereed proceedings of the 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020 held in Taiyuan, China, in September 2020. The 98 papers presented in these two volumes were carefully reviewed and selected from 392 submissions. The papers are organized in topical sections: database, machine learning, network, graphic images, system, natural language processing, security, algorithm, application, and education.The chapter “Highly Parallel SPARQL Engine for RDF” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Data Science: 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020, Taiyuan, China, September 18-21, 2020, Proceedings, Part II (Communications in Computer and Information Science #1258)
by Hongzhi Wang Guanglu Sun Zeguang Lu Pinle QinThis two volume set (CCIS 1257 and 1258) constitutes the refereed proceedings of the 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020 held in Taiyuan, China, in September 2020. The 98 papers presented in these two volumes were carefully reviewed and selected from 392 submissions. The papers are organized in topical sections: database, machine learning, network, graphic images, system, natural language processing, security, algorithm, application, and education.
Data Science: 6th International Conference, ICDS 2019, Ningbo, China, May 15–20, 2019, Revised Selected Papers (Communications in Computer and Information Science #1179)
by Yong Shi Philip S. Yu Jie Cao Xingsen Li Jing He Guangyan Huang Zhijun Xie Fu XiaoThis book constitutes the refereed proceedings of the 6th International Conference on Data Science, ICDS 2019, held in Ningbo, China, during May 2019. The 64 revised full papers presented were carefully reviewed and selected from 210 submissions. The research papers cover the areas of Advancement of Data Science and Smart City Applications, Theory of Data Science, Data Science of People and Health, Web of Data, Data Science of Trust and Internet of Things.
Data Science: 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021, Taiyuan, China, September 17–20, 2021, Proceedings, Part I (Communications in Computer and Information Science #1451)
by Weipeng Jing Xianhua Song Zeguang Lu Pinle Qin Jianchao ZengThis two volume set (CCIS 1451 and 1452) constitutes the refereed proceedings of the 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021 held in Taiyuan, China, in September 2021.The 81 papers presented in these two volumes were carefully reviewed and selected from 256 submissions. The papers are organized in topical sections on big data management and applications; social media and recommendation systems; infrastructure for data science; basic theory and techniques for data science; machine learning for data science; multimedia data management and analysis; social media and recommendation systems; data security and privacy; applications of data science; education research, methods and materials for data science and engineering; research demo.
Data Science: 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021, Taiyuan, China, September 17–20, 2021, Proceedings, Part II (Communications in Computer and Information Science #1452)
by Weipeng Jing Xianhua Song Zeguang Lu Pinle Qin Jianchao ZengThis two volume set (CCIS 1451 and 1452) constitutes the refereed proceedings of the 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021 held in Taiyuan, China, in September 2021.The 81 papers presented in these two volumes were carefully reviewed and selected from 256 submissions. The papers are organized in topical sections on big data management and applications; social media and recommendation systems; infrastructure for data science; basic theory and techniques for data science; machine learning for data science; multimedia data management and analysis; social media and recommendation systems; data security and privacy; applications of data science; education research, methods and materials for data science and engineering; research demo.
Data Science: 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022, Chengdu, China, August 19–22, 2022, Proceedings, Part I (Communications in Computer and Information Science #1628)
by Yang Wang Qilong Han Hongzhi Wang Xianhua Song Zeguang Lu Guobin ZhuThis 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 Mining and Knowledge Management; Machine Learning for Data Science; Multimedia Data Management and Analysis.
Data Science: 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022, Chengdu, China, August 19–22, 2022, Proceedings, Part II (Communications in Computer and Information Science #1629)
by Yang Wang Qilong Han Xianhua Song Zeguang Lu Guobin Zhu Liehui ZhangThis 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.