Download or read book Data Science Learning by Latent Structures and Knowledge Discovery written by Berthold Lausen and published by Springer. This book was released on 2015-05-06 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 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.

Download or read book The Essentials of Data Science Knowledge Discovery Using R written by Graham J. Williams and published by CRC Press. This book was released on 2017-07-28 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Essentials of Data Science: Knowledge Discovery Using R presents the concepts of data science through a hands-on approach using free and open source software. It systematically drives an accessible journey through data analysis and machine learning to discover and share knowledge from data. Building on over thirty years’ experience in teaching and practising data science, the author encourages a programming-by-example approach to ensure students and practitioners attune to the practise of data science while building their data skills. Proven frameworks are provided as reusable templates. Real world case studies then provide insight for the data scientist to swiftly adapt the templates to new tasks and datasets. The book begins by introducing data science. It then reviews R’s capabilities for analysing data by writing computer programs. These programs are developed and explained step by step. From analysing and visualising data, the framework moves on to tried and tested machine learning techniques for predictive modelling and knowledge discovery. Literate programming and a consistent style are a focus throughout the book.

Download or read book SOFSEM 2023 Theory and Practice of Computer Science written by Leszek Gąsieniec and published by Springer Nature. This book was released on 2022-12-19 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the conference proceedings of the 48th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2023, held in Nový Smokovec, Slovakia, during January 15–18, 2023. The 22 full papers presented together with 2 best papers and 2 best students papers in this book were carefully reviewed and selected from 43 submissions. This workshop focuses on graphs problems and optimization; graph drawing and visualization; NP-hardness and fixed parameter tractability; communication and temporal graphs; complexity and learning; and robots and strings.

Download or read book Data Science and Machine Learning written by Dirk P. Kroese and published by CRC Press. This book was released on 2019-11-20 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code

Download or read book Feature Engineering for Machine Learning and Data Analytics written by Guozhu Dong and published by CRC Press. This book was released on 2018-03-14 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little can be achieved if there are few features to represent the underlying data objects, and the quality of results of those algorithms largely depends on the quality of the available features. Feature Engineering for Machine Learning and Data Analytics provides a comprehensive introduction to feature engineering, including feature generation, feature extraction, feature transformation, feature selection, and feature analysis and evaluation. The book presents key concepts, methods, examples, and applications, as well as chapters on feature engineering for major data types such as texts, images, sequences, time series, graphs, streaming data, software engineering data, Twitter data, and social media data. It also contains generic feature generation approaches, as well as methods for generating tried-and-tested, hand-crafted, domain-specific features. The first chapter defines the concepts of features and feature engineering, offers an overview of the book, and provides pointers to topics not covered in this book. The next six chapters are devoted to feature engineering, including feature generation for specific data types. The subsequent four chapters cover generic approaches for feature engineering, namely feature selection, feature transformation based feature engineering, deep learning based feature engineering, and pattern based feature generation and engineering. The last three chapters discuss feature engineering for social bot detection, software management, and Twitter-based applications respectively. This book can be used as a reference for data analysts, big data scientists, data preprocessing workers, project managers, project developers, prediction modelers, professors, researchers, graduate students, and upper level undergraduate students. It can also be used as the primary text for courses on feature engineering, or as a supplement for courses on machine learning, data mining, and big data analytics.

Download or read book Introduction to Random Graphs written by Alan Frieze and published by Cambridge University Press. This book was released on 2016 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text covers random graphs from the basic to the advanced, including numerous exercises and recommendations for further reading.

Download or read book Analysis of Large and Complex Data written by Adalbert F.X. Wilhelm and published by Springer. This book was released on 2016-08-03 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields. The contributions span a broad spectrum, from theoretical developments to practical applications; they all share a strong computational component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and Knowledge Discovery; Data Analysis in Marketing; Data Analysis in Finance and Economics; Data Analysis in Medicine and the Life Sciences; Data Analysis in the Social, Behavioural, and Health Care Sciences; Data Analysis in Interdisciplinary Domains; Classification and Subject Indexing in Library and Information Science. The book presents selected papers from the Second European Conference on Data Analysis, held at Jacobs University Bremen in July 2014. This conference unites diverse researchers in the pursuit of a common topic, creating truly unique synergies in the process.

Download or read book Marketing Analytics Creating Customer Centric Culture written by Joseph B. Rivera and published by Joseph B. Rivera. This book was released on 2020-02-17 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: A game-changing approach to marketing by an experienced author, speaker and businessman Joseph B. Rivera. Joseph B. Rivera has first-hand experience in business. He has learned everything through hard work and perseverance, and has inspired quite a lot of entrepreneurs, businessmen, executives, employees, and business students to challenge themselves in this modern era of commerce. For the first time, Joseph B. Rivera offers his years of experience and wisdom in this one compact, very accessible and enduring masterpiece. MARKETING ANALYTICS: CREATING CUSTOMER-CENTRIC CULTURE helps you to create a transformative culture toward excellence in your business. Whether you are an executive, businessman, business owner, investor, marketer, trainer, speaker or a student of marketing, you will be proud of what you will learn. When applied right, you will change the way products and services are designed, created and offered to the world. This book teaches you how to meaningfully connect emotionally and practically to your consumers. Remember, it is not just all about the money. Here, Joseph has put together his passion, insights, observation and experience to mentor you: ✔️How to understand the needs of the market. ✔️How to position your business. ✔️How to overcome competition. ✔️How to revolutionize your business. Learn the art or marketing analytics, and be a game changer.

Download or read book Intelligent Information and Database Systems written by Ngoc Thanh Nguyen and published by Springer Nature. This book was released on 2020-03-03 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 12033 and 11034 constitutes the refereed proceedings of the 12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020, held in Phuket, Thailand, in March 2020. The total of 105 full papers accepted for publication in these proceedings were carefully reviewed and selected from 285 submissions. The papers of the first volume are organized in the following topical sections: Knowledge Engineering and Semantic Web, Natural Language Processing, Decision Support and Control Systems, Computer Vision Techniques, Machine Learning and Data Mining, Deep Learning Models, Advanced Data Mining Techniques and Applications, Multiple Model Approach to Machine Learning. The papers of the second volume are divided into these topical sections: Application of Intelligent Methods to Constrained Problems, Automated Reasoning with Applications in Intelligent Systems, Current Trends in Arti cial Intelligence, Optimization, Learning,and Decision-Making in Bioinformatics and Bioengineering, Computer Vision and Intelligent Systems, Data Modelling and Processing for Industry 4.0, Intelligent Applications of Internet of Things and Data AnalysisTechnologies, Intelligent and Contextual Systems, Intelligent Systems and Algorithms in Information Sciences, Intelligent Supply Chains and e-Commerce, Privacy, Security and Trust in Arti cial Intelligence, Interactive Analysis of Image, Video and Motion Data in LifeSciences.

Download or read book Advances in Computational Intelligence written by Ildar Batyrshin and published by Springer Nature. This book was released on 2021-10-20 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 13067 and 13068 constitutes the proceedings of the 20th Mexican International Conference on Artificial Intelligence, MICAI 2021, held in Mexico City, Mexico, in October 2021. The total of 58 papers presented in these two volumes was carefully reviewed and selected from 129 submissions. The first volume, Advances in Computational Intelligence, contains 30 papers structured into three sections: – Machine and Deep Learning – Image Processing and Pattern Recognition – Evolutionary and Metaheuristic Algorithms The second volume, Advances in Soft Computing, contains 28 papers structured into two sections: – Natural Language Processing – Intelligent Applications and Robotics

Download or read book Methods for Analyzing and Leveraging Online Learning Data written by Hai-Jew, Shalin and published by IGI Global. This book was released on 2018-10-05 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: While online learning continues to be a rapidly expanding field of research, analyzing data allows educational institutions to fine tune their curriculum and teaching methods. Properly utilizing the data, however, becomes difficult when taking into account how socio-technical systems are used, the administration of those systems, default settings, how data is described and captured, and other factors. Methods for Analyzing and Leveraging Online Learning Data is a pivotal reference source that provides vital research on the application of data in online education for improving a system’s capabilities and optimizing it for teaching and learning. This publication explores data handling, cleaning, analysis, management, and representation, as well as the methods of effectively and ethically applying data research. Tying together education and information science with special attention paid to informal learning, online assessment, and social media, this book is ideally designed for educational administrators, system developers, curriculum designers, data analysts, researchers, instructors, and graduate-level students seeking current research on capturing, analyzing, storing, and sharing data-analytic insights regarding online learning environments.

Download or read book Algorithms and Models for the Web Graph written by Anthony Bonato and published by Springer. This book was released on 2016-11-10 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 13th International Workshop on Algorithms and Models for the Web Graph, WAW 2016, held in Montreal, QC, Canada, in December 2016. The 13 full papers presented in this volume were carefully reviewed and selected from 14 submissions. The workshop gathered the researchers who are working on graph-theoretic and algorithmic aspects of related complex networks, including social networks, citation networks, biological networks, molecular networks, and other networks arising from the Internet.

Download or read book Algorithms and Models for Network Data and Link Analysis written by François Fouss and published by Cambridge University Press. This book was released on 2016-07-12 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network data are produced automatically by everyday interactions - social networks, power grids, and links between data sets are a few examples. Such data capture social and economic behavior in a form that can be analyzed using powerful computational tools. This book is a guide to both basic and advanced techniques and algorithms for extracting useful information from network data. The content is organized around 'tasks', grouping the algorithms needed to gather specific types of information and thus answer specific types of questions. Examples include similarity between nodes in a network, prestige or centrality of individual nodes, and dense regions or communities in a network. Algorithms are derived in detail and summarized in pseudo-code. The book is intended primarily for computer scientists, engineers, statisticians and physicists, but it is also accessible to network scientists based in the social sciences. MATLAB®/Octave code illustrating some of the algorithms will be available at: http://www.cambridge.org/9781107125773.

Download or read book Synergies Between Knowledge Engineering and Software Engineering written by Grzegorz J. Nalepa and published by Springer. This book was released on 2017-09-15 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book compiles a number of contributions originating from the KESE (Knowledge Engineering and Software Engineering) workshop series from 2005 to 2015. The idea behind the series was the realignment of the knowledge engineering discipline and its strong relation to software engineering, as well as to the classical aspects of artificial intelligence research. The book introduces symbiotic work combining these disciplines, such as aspect-oriented and agile engineering, using anti-patterns, and system refinement. Furthermore, it presents successful applications from different areas that were created by combining techniques from both areas.

Download or read book Reengineering Corporate Communication written by Uwe Seebacher and published by Springer Nature. This book was released on 2022-07-28 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book employs the latest insights from modern marketing into the theory and practice of corporate communication, including the main stages and goals, and highlights the key potentials for the field. It briefly presents the essential features of the methodological and structural sciences in order to illustrate to the reader how, from a marketer's point of view, these new insights can be derived objectively, reliably, and validly for the field of corporate communication according to scientific criteria. The book then introduces the maturity model for modern corporate communication and describes which fields of activity must be gone through in order to be able to implement the change management process towards corporate communication excellence efficiently and effectively. Building on this, it introduces and defines the most important new concepts of corporate communication in the twenty-first century and thus clearly delineates the field of research for this corporate function in the coming years. The book goes on to address the important areas of IT and HR in order to provide a 360° view of the developments to be realized in the field of corporate communication. A “CC self-test” at the end of the book is intended to help the reader immediately recognize where their own organization stands and, against this backdrop, to be able to start the necessary activities towards corporate communication excellence immediately on the basis of the maturity model. “Prof. Dr. Uwe Seebacher takes us on a timely and informative read on what could be the biggest crisis for Corporate Communications – remaining stagnant in a time of great change. With rich context and fine detail, he illuminates the opportunities to reengineer Corporate Communications and quantify its role in truly impacting business. From the importance of predictive intelligence underpinned by authenticity and empathy to building trust, this book is a guide for successful business in the 21st Century. I highly recommend it.” Heidi Eusebio, Strategist and Executive Director, Edelman "Uwe Seebacher has once again demonstrated in a well-founded manner what methodological and structural science is capable of - namely, to precisely logically derive the long overdue process of change in the field of corporate communications and thereby make it comprehensible. But he also takes the important next step of operationalizing his thoughts in a directly measurable way by providing an easy applicable concrete process model for reengineering corporate communication with many tips, templates and inputs for HR and IT.“ Miguel Gimenez de Castro, Head Of Communications Spain, Portugal, Greece and Israel, IBM

Download or read book Artificial Neural Networks and Machine Learning ICANN 2018 written by Věra Kůrková and published by Springer. This book was released on 2018-09-25 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The 139 full and 28 short papers as well as 41 full poster papers and 41 short poster papers presented in these volumes was carefully reviewed and selected from total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection, Multilayer Perceptrons and Kernel Networks, Natural Language, Object and Face Recognition, Recurrent Neural Networks and Reservoir Computing, Reinforcement Learning, Reservoir Computing, Self-Organizing Maps, Spiking Dynamics/Spiking ANN, Support Vector Machines, Swarm Intelligence and Decision-Making, Text Mining, Theoretical Neural Computation, Time Series and Forecasting, Training and Learning.

Download or read book Artificial Neural Networks and Machine Learning ICANN 2022 written by Elias Pimenidis and published by Springer Nature. This book was released on 2022-09-06 with total page 817 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 4-volumes set of LNCS 13529, 13530, 13531, and 13532 constitutes the proceedings of the 31st International Conference on Artificial Neural Networks, ICANN 2022, held in Bristol, UK, in September 2022. The total of 255 full papers presented in these proceedings was carefully reviewed and selected from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artificial neural networks, with strong cross-disciplinary interactions and applications.