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Suggestions : Analyse des données & data mining
Advanced introduction to spatial statistics
Advanced introduction to spatial statistics [texte imprimé] / Daniel A. Griffith (1948-....) ; Bin Li . - Cheltenham (GBR) ; Camberley (GBR) ; Northampton, MA : Edward Elgar, 2022 . - xviii-178 p. : fig.,tabl. ; 22 cm. - (Elgar Advanced introductions series, ISSN 2514-8168) .ISBN : 978-1-80037-283-2Bibliogr. p. 153-164. IndexLangues : Anglais (eng)Descripteurs : Analyse spatiale , Estimation d'un modèle , Géostatistique , Modélisation , Variable aléatoire Tags : Geospatial data Spatial analysis (Statistics) Index. décimale : 258 Géostatistique - Environnemétrie Résumé : This Advanced Introduction provides a critical review and discussion of research concerning spatial statistics, differentiating between it and spatial econometrics, to answer a set of core questions covering the geographic-tagging-of-data origins of the concept and its theoretical underpinnings, conceptual advances, and challenges for future scholarly work. It offers a vital tool for understanding spatial statistics and surveys how concerns about violating the independent observations assumption of statistical analysis developed into this discipline. [D'après le résumé de l'éditeur] Note de contenu : Autre ISBN (Relié) = 978-1800372818 En ligne : https://www.e-elgar.com/shop/gbp/advanced-introduction-to-spatial-statistics-978 [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=170988 
Analyzing textual information : from words to meanings through numbers [texte imprimé] / Johannes Ledolter ; Lea S. VanderVelde . - Thousand Oaks, CA ; Londres : SAGE Publications, 2021 . - xix, 168 p. : ill. ; 22 cm. - (Quantitative applications in the social sciences, ISSN 0149-192X; 188) .ISBN : 978-1-5443-9000-0Notes bibliogr.Langues : Anglais (eng)Descripteurs : Analyse des données , Données massives , Logiciel statistique R , Sciences sociales , Statistique mathématique Tags : Social sciences Methodology Analyse d'informations textuelles Données textuelles Analyse quantitative des données textuelles Index. décimale : 232 Analyse des données Résumé : Researchers in the social sciences and beyond are dealing more and more with massive quantities of text data requiring analysis, from historical letters to the constant stream of content in social media. Traditional texts on statistical analysis have focused on numbers, but this book will provide a practical introduction to the quantitative analysis of textual data. Using up-to-date R methods, this book will take readers through the text analysis process, from text mining and pre-processing the text to final analysis. It includes two major case studies using historical and more contemporary text data to demonstrate the practical applications of these methods. Currently, there is no introductory how-to book on textual data analysis with R that is up-to-date and applicable across the social sciences. Code and a variety of additional resources are available on an accompanying website for the book. [D'après le résumé de l'éditeur] Note de contenu : . Mise à jour 09/02/23 En ligne : https://us.sagepub.com/en-us/nam/analyzing-textual-information/book270847?priori [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=165682 
ANOVA and mixed models : a short introduction using R [texte imprimé] / Lukas Meier . - Boca Raton, FL ; Londres : Chapman and Hall/CRC Press : Londres ; New York ; Abingdon ; Oxon : Routledge, 2022 . - 201 p. : ill. ; 25 cm. - (Chapman & Hall/CRC The R series) .ISBN : 978-0-367-70420-9Bibliogr. p. . IndexLangues : Anglais (eng)Descripteurs : Analyse en composantes multiples , Logiciel statistique R , Statistique exploratoire multidimensionnelle , Statistique mathématique , Statistique multidimensionnelle Tags : ANOVA Mixed models Index. décimale : 219 Statistique descriptive multidimensionnelle Résumé : This book presents ANOVA and Mixed models, with R, provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs. Based on knowledge from an introductory course on probability and statistics, the theoretical foundations of the most important models are introduced. [D'après le résumé de l'éditeur] Note de contenu : Hardback (2022) : ISBN = 978-0-367-70422-3. Mise à jour 09/02/23 En ligne : https://www.routledge.com/ANOVA-and-Mixed-Models-A-Short-Introduction-Using-R/Me [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=171561 
Big data [texte imprimé] / Wolfgang Pietsch . - Cambridge (GBR) ; West Nyack, NY : CUP. Cambridge University Press, 2021 . - 86 p. ; 23 cm. - (Elements in the Philosophy of Science) .ISBN : 978-1-108-70669-8Langues : Anglais (eng)Descripteurs : Algorithme mathématique , Analyse des données , Apprentissage automatique , Données massives , Epistémologie , Philosophie Tags : Big data Méthodes d'analyse de grands ensembles de données Étude épistémologique Index. décimale : 239 Fouille de données - Data mining Résumé : Big Data and methods for analyzing large data sets such as machine learning have in recent times deeply transformed scientific practice in many fields. However, an epistemological study of these novel tools is still largely lacking. After a conceptual analysis of the notion of data and a brief introduction into the methodological dichotomy between inductivism and hypothetico-deductivism, several controversial theses regarding big data approaches are discussed. These include, whether correlation replaces causation, whether the end of theory is in sight and whether big data approaches constitute entirely novel scientific methodology. [D'après le résumé de l'éditeur] Note de contenu : Mise à jour 06/08/21. Mise à jour 23/12/21. Mise à jour 01/06/22. Mise à jour 21/10/22. Mise à jour 09/02/23 En ligne : https://www.cambridge.org/fr/academic/subjects/philosophy/philosophy-science/big [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=164854 
Big data [texte imprimé] / Benoit LeClerc ; Benoit LeClerc, Éditeur scientifique ; Jesse Cale, Éditeur scientifique . - Londres ; New York ; Abingdon ; Oxon : Routledge, 2022 . - 148 p. ; 24 cm. - (Criminology at the Edge) .ISBN : 978-1-03-233699-2Langues : Anglais (eng)Descripteurs : Analyse des données , Données massives Tags : Criminology Data processing Big data Index. décimale : 232 Analyse des données Résumé : The Internet has launched the world into an era into which enormous amounts of data are generated every day through technologies with both positive and negative consequences. This often refers to Big Data. This book explores Big Data in organisations operating in the criminology and criminal justice fields. Big Data entails a major disruption in the ways we think about and do things, which certainly applies to most organisations including those operating in the criminology and criminal justice fields. Big Data is currently disrupting processes in most organisations - how different organisations collaborate with one another, how organisations develop products or services, how organisations can identify, recruit and evaluate talent, how organisations can make better decisions based on empirical evidence rather than intuition, and how organisations can quickly implement any transformation plan, to name a few. [D'après le résumé de l'éditeur] Note de contenu : Hardback = ISBN: 978-1-138-49278-3 (2020). Mise à jour 10/06/22. Mise à jour 21/10/22. Mise à jour 09/02/23 En ligne : https://www.routledge.com/Big-Data/Leclerc-Cale/p/book/9781032336992 Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=171477 Communicating with data visualisation
Communicating with data visualisation : a practical guide [texte imprimé] / Adam Frost ; Tobias Sturt ; Jim Kynvin ; Sergio Fernandez Gallardo . - Thousand Oaks, CA ; Londres : SAGE Publications, 2021 . - 368 p. ; 24 cm.ISBN : 978-1-5297-4377-7Langues : Anglais (eng)Descripteurs : Fouille de données , Représentation graphique Tags : Visualisation de données Statistiques Graphiques Cartes statiques Infographie Index. décimale : 239 Fouille de données - Data mining Résumé : How can you transform a spreadsheet of numbers into a clear, compelling story that your audience will want to pass on? This book is a step-by-step guide to bringing data to life through visualisations, from static charts and maps to interactive infographics and motion graphics. Introducing a four-step framework to creating engaging and innovative visualisations, it helps you to: · Find the human stories in your datasets · Design a visual story that will resonate with your audience · Make a clear, persuasive visual that represents your data truthfully · Refine your work to ensure your visual expresses your story in the best possible way. This book also includes a portfolio of best-practice examples and annotated templates to help you choose the right visual for the right audience, and repurpose your work for different contexts. [Résumé de l'éditeur] Note de contenu : Hardcover : ISBN = 978-1-5297-4376-0 . Mise à jour 09/02/23 En ligne : https://us.sagepub.com/en-us/nam/communicating-with-data-visualisation/book27505 [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=170511 
Compressive imaging : structure, sampling, learning [texte imprimé] / Ben Adcock ; Anders C. Hansen . - Cambridge (GBR) ; West Nyack, NY : CUP. Cambridge University Press, 2021 . - xv, 601 p. : ill. ; 25 cm.ISBN : 978-1-108-42161-4Bibliogr.Langues : Anglais (eng)Descripteurs : Apprentissage automatique , Échantillonnage , Ondelette , Optimisation , Réseaux de neurones , Traitement du signal Tags : Image compression Digital images Deconvolution Imagerie compressive Reconstruction d'image précise Apprentissage profond Index. décimale : 256 Traitement du signal et de l'image Résumé : Accurate, robust and fast image reconstruction is a critical task in many scientific, industrial and medical applications. Over the last decade, image reconstruction has been revolutionized by the rise of compressive imaging. It has fundamentally changed the way modern image reconstruction is performed. This in-depth treatment of the subject commences with a practical introduction to compressive imaging, supplemented with examples and downloadable code, intended for readers without extensive background in the subject. Next, it introduces core topics in compressive imaging – including compressed sensing, wavelets and optimization – in a concise yet rigorous way, before providing a detailed treatment of the mathematics of compressive imaging. The final part is devoted to recent trends in compressive imaging: deep learning and neural networks. With an eye to the next decade of imaging research, and using both empirical and mathematical insights, it examines the potential benefits and the pitfalls of these latest approaches. [D'après le résumé de l'éditeur] Note de contenu : . Mise à jour 09/02/23 En ligne : https://www.cambridge.org/fr/academic/subjects/mathematics/computational-science [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=173138 Computational topology for data analysis
Computational topology for data analysis [texte imprimé] / Tamal K. Dey ; Yusu Wang . - Cambridge (GBR) ; West Nyack, NY : CUP. Cambridge University Press, 2022 . - 450 p. ; 23 cm.ISBN : 978-1-00-909816-8Langues : Anglais (eng)Descripteurs : Analyse des données , Apprentissage automatique , Topologie Tags : Topology Topologie informatique Analyse des données topologiques (TDA) Analyse de données complexes Nuages de points Triangulation Données graphiques Théorie Morse discrète Structure Mapper Index. décimale : 232 Analyse des données Résumé : Topological data analysis (TDA) has emerged recently as a viable tool for analyzing complex data, and the area has grown substantially both in its methodologies and applicability. Providing a computational and algorithmic foundation for techniques in TDA, this text introduces students and researchers in mathematics and computer science to the current state of the field. The book features a description of mathematical objects and constructs behind recent advances, the algorithms involved, computational considerations, as well as examples of topological structures or ideas that can be used in applications. It provides a thorough treatment of persistent homology together with various extensions – like zigzag persistence and multiparameter persistence – and their applications to different types of data, like point clouds, triangulations, or graph data. Other important topics covered include discrete Morse theory, the Mapper structure, optimal generating cycles, as well as recent advances in embedding TDA within machine learning frameworks. [D'après le résumé de l'éditeur] Note de contenu : Mise à jour 15/04/22. Mise à jour 10/06/22. Mise à jour 21/10/22. Mise à jour 09/02/23 En ligne : https://www.cambridge.org/fr/academic/subjects/mathematics/geometry-and-topology [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=170598 Data analytics for cybersecurity
Data analytics for cybersecurity [texte imprimé] / Vandana P. Janeja . - Cambridge (GBR) ; West Nyack, NY : CUP. Cambridge University Press, 2022 . - 240 p. ; 23 cm.ISBN : 978-1-108-41527-9Langues : Anglais (eng)Descripteurs : Analyse des données , Analyse spatiale , Fouille de données , Programmation orientée objet , Sécurité informatique , Série temporelle , Statistique exploratoire multidimensionnelle Tags : Computer security Data processing Data mining Computers security Cybersécurité Cybermenaces Approche orientée données Détection d'anomalies Analyse multidomaine Séries chronologiques Aanalyse des données spatiales Index. décimale : 239 Fouille de données - Data mining Résumé : As the world becomes increasingly connected, it is also more exposed to a myriad of cyber threats. We need to use multiple types of tools and techniques to learn and understand the evolving threat landscape. Data is a common thread linking various types of devices and end users. Analyzing data across different segments of cybersecurity domains, particularly data generated during cyber-attacks, can help us understand threats better, prevent future cyber-attacks, and provide insights into the evolving cyber threat landscape. This book takes a data oriented approach to studying cyber threats, showing in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity, such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity. [D'après le résumé de l'éditeur] Note de contenu : . Mise à jour 10/06/22. Mise à jour 21/10/22. Mise à jour 09/02/23 En ligne : https://www.cambridge.org/fr/academic/subjects/computer-science/communications-i [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=171204 Data-driven science and engineering
Data-driven science and engineering : machine learning, dynamical systems, and control [texte imprimé] / Steven L. Brunton ; Jose Nathan Kutz . - 2nd edition . - Cambridge (GBR) ; West Nyack, NY : CUP. Cambridge University Press, 2022 . - 550 p. ; 25 cm.ISBN : 978-1-00-909848-9Langues : Anglais (eng)Descripteurs : Analyse des données , Apprentissage automatique , Mesure (Théorie) , Modélisation , Optimisation Tags : Science des données Ingénierie des données Python MATLAB Physique mathématique Intégration de la modélisation Apprentissage par renforcement Deep learning Index. décimale : 232 Analyse des données Résumé : Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering a broad overview of the growing intersection of data-driven methods, machine learning, applied optimization, and classical fields of engineering mathematics and mathematical physics. With a focus on integrating dynamical systems modeling and control with modern methods in applied machine learning, this text includes methods that were chosen for their relevance, simplicity, and generality. Topics range from introductory to research-level material, making it accessible to advanced undergraduate and beginning graduate students from the engineering and physical sciences. The second edition features new chapters on reinforcement learning and physics-informed machine learning, significant new sections throughout, and chapter exercises. Online supplementary material including lecture videos per section, homeworks, data, and codes in MATLAB, Python, and Julia available on databookuw.com. [D'après le résumé de l'éditeur] Note de contenu : Mise à jour 14/03/22. Mise à jour 01/06/22. Mise à jour 21/10/22. Mise à jour 09/02/23 En ligne : https://www.cambridge.org/fr/academic/subjects/mathematics/computational-science [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=170702 
Data mining and exploration : from traditional statistics to modern data science [texte imprimé] / Chong Ho Alex Yu . - Boca Raton, FL ; Londres : Chapman and Hall/CRC Press : Londres ; New York ; Abingdon ; Oxon : Routledge, 2022 . - 290 p. : ill. ; 25 cm.ISBN : 978-0-367-72146-6Langues : Anglais (eng)Descripteurs : Analyse des données , Fouille de données Tags : Data Mining Exploration de données Index. décimale : 239 Fouille de données - Data mining Résumé : This book introduces both conceptual and procedural aspects of cutting-edge data science methods, such as dynamic data visualization, artificial neural networks, ensemble methods, and text mining. There are at least two unique elements that can set the book apart from its rivals. Most students in social sciences, engineering, and business took at least one class in introductory statistics before learning data science. However, usually these courses do not discuss the similarities and differences between these two schools of thought, and as a result learners are disoriented by this seemingly drastic paradigm shift. In reaction, some traditionalists reject data science altogether while some beginning data analysts employ data mining tools as a "black box", without a comprehensive view of the foundational differences between traditional and modern methods (e.g. dichotomous thinking vs. pattern recognition, confirmation vs. exploration, single method vs. triangulation, single sample vs. cross-validation...etc.). To remediate this problem, this book will provide the readers with the details of the similarities and differences between classical methods and data science, as well as the path for the transition (e.g. from p value to LogWorth, from resampling to ensemble methods, from content analysis to text mining...etc.). [D'après le résumé de l'éditeur] Note de contenu : . Mise à jour 09/02/23 En ligne : https://www.routledge.com/Data-Mining-and-Exploration-From-Traditional-Statistic [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=171560 Data visualization for social and policy research
Data visualization for social and policy research : a step-by-step approach using R and Python [texte imprimé] / Jose Manuel Magallanes Reyes . - Cambridge (GBR) ; West Nyack, NY : CUP. Cambridge University Press, 2022 . - 280 p. : ill. ; 23 cm.ISBN : 978-1-108-71438-9Bibliogr. p. . IndexLangues : Anglais (eng)Descripteurs : Analyse des données , Fouille de données , Logiciel statistique R , Sciences politiques , Sciences sociales , Série temporelle Tags : Visualisation des données Recherche sociale Recherche politique Python Index. décimale : 239 Fouille de données - Data mining Résumé : All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website. It includes multiple visualization techniques for all different of data types and data structures, including time series, maps and text visualization. It offers step by step explanations in both R and Python, with comparison of the two languages. Examples are drawn from across the social sciences, including, public policy, education, and health. [D'après le résumé de l'éditeur] Note de contenu : Hardback = ISBN: 978-1-108-49433-5.- Mise à jour 25/05/22. Mise à jour 20/10/22. Mise à jour 19/01/23. Mise à jour 13/02/23 En ligne : https://www.cambridge.org/fr/academic/subjects/statistics-probability/statistics [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=171019 A history of data visualization and graphic communication
A history of data visualization and graphic communication [texte imprimé] / Michael Friendly ; Howard Wainer (1943-....) . - Cambridge, MA : Harvard University Press, 2021 . - 320 p. ; 25 cm.ISBN : 978-0-674-97523-1Langues : Anglais (eng)Descripteurs : Etude historique , Fouille de données , Graphes (Théorie) Tags : Information visualization Visual communication Graphic methods Visual analytics Visualisation de données Index. décimale : 239 Fouille de données - Data mining Résumé : Statistical graphing was born in the seventeenth century as a scientific tool, but it quickly escaped all disciplinary bounds. Today graphics are ubiquitous in daily life. This book details the history of data visualization and argue that it has not only helped us solve problems, but it has also changed the way we think. It rises and effects on the ways we think about and solve problems. With complex information everywhere, graphics have become indispensable to our daily lives. Navigation apps show real-time, interactive traffic data. A color-coded map of exit polls details election balloting down to the county level. Charts communicate stock market trends, government spending, and the dangers of epidemics. The book tells the story of how graphics left the exclusive confines of scientific research and became ubiquitous. As data visualization spread, it changed the way we think. [D'après le résumé de l'éditeur] Note de contenu : . Mise à jour 09/02/23 En ligne : https://www.hup.harvard.edu/catalog.php?isbn=9780674975231 Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=165668 
Il était une fois sur cent : rêveries fragmentaires sur l’emprise statistique [texte imprimé] / Yves Pagès (1963-....) . - Paris : Éditions Zones, 2021 . - 128 p. : ill. ; 21 cm.ISBN : 978-2-35522-170-5Langues : Français (fre)Descripteurs : Statistique descriptive Index. décimale : 201 Statistique descriptive - Indices Résumé : Par-delà cet art du détournement stylistique, il nous livre en pointillé une analyse caustique de la condition des vivants à l’ère de la gouvernance par les nombres, agrémentée de quelques suggestions paradoxales pour passer entre les mailles du filet statistique. [D'après le résumé de l'éditeur] Note de contenu : . Mise à jour 06/08/21. Mise à jour 23/12/21. Mise à jour 01/06/22. Mise à jour 21/10/22. Mise à jour 09/02/23 En ligne : https://www.editions-zones.fr/livres/il-etait-une-fois-sur-cent/ Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=165491 Information-theoretic methods in data science
Information-theoretic methods in data science [texte imprimé] / Miguel R. D. Rodrigues, Éditeur scientifique ; Yonina C. Eldar, Éditeur scientifique . - Cambridge (GBR) ; West Nyack, NY : CUP. Cambridge University Press, 2021 . - 560 p. : ill. ; 25 cm.ISBN : 978-1-108-42713-5Bibliogr. p. . IndexLangues : Anglais (eng)Descripteurs : Analyse des données , Apprentissage automatique , Fouille de données , Information (Théorie) , Statistique mathématique Tags : Data Science Information theory Méthodes théoriques de l'information Science des données Acquisition de données Représentation des données Acquisition du signal Compression des données Détection compressive Communication des données étudiants diplômés et les chercheurs travaillant en théorie de l'information traitement du signal Index. décimale : 219 Statistique descriptive multidimensionnelle Résumé : Learn about the state-of-the-art at the interface between information theory and data science with this first unified treatment of the subject. This book is clear, in a tutorial style, and using consistent notation and definitions throughout; it shows how information-theoretic methods are being used in data acquisition, data representation, data analysis, and statistics and machine learning. Coverage is broad, with chapters on signal acquisition, data compression, compressive sensing, data communication, representation learning, emerging topics in statistics, and much more. Each chapter includes a topic overview, definition of the key problems, emerging and open problems, and an extensive reference list, allowing readers to develop in-depth knowledge and understanding. Providing a thorough survey of the current research area and cutting-edge trends, this is essential reading for graduate students and researchers working in information theory, signal processing, machine learning, and statistics. [D'après le résumé de l'éditeur] Note de contenu : Mise à jour 26/01/21. Mise à jour 08/04/21. Mise à jour 06/08/21. Mise à jour 15/12/21. Mise à jour 26/04/22. Mise à jour 01/06/22. Mise à jour 21/10/22. Mise à jour 09/02/23 En ligne : https://www.cambridge.org/fr/academic/subjects/engineering/communications-and-si [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=150158 
Introduction to data science : data analysis and prediction ; algorithms with R [texte imprimé] / Rafael A. Irizarry . - Boca Raton, FL ; Londres : Chapman and Hall/CRC Press, 2020 . - XXX-713 p. : ill. ; 26 cm. - (Chapman & Hall/CRC Data science series) .ISBN : 978-0-367-35798-6Langues : Anglais (eng)Descripteurs : Apprentissage automatique , Fouille de données Tags : Data visualisation Algorithmes Statistiques Exploration de données Index. décimale : 239 Fouille de données - Data mining Résumé : This text introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert. [D'après le résumé de l'éditeur] Note de contenu : Mise à jour 24/11/22. Mise à jour 19/01/23. Mise à jour 20/02/23 En ligne : https://www.routledge.com/Introduction-to-Data-Science-Data-Analysis-and-Predict [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=171500 
Kafka : the definitive guide : real-time data and stream processing at scale [texte imprimé] / Gwen Shapira ; Todd Palino ; Rajini Sivaram, ; Krit Petty, . - 2nd edition . - Sebastopol, CA ; Cambridge (GBR) : O'Reilly, 2021 . - p. : fig. ; 24 cm.ISBN : 978-1-4920-4308-9IndexLangues : Anglais (eng)Descripteurs : Données massives , Traitement des données Tags : Apache Kafka Traitement des des flux Plateforme de streaming open source Clusters Kafka Big Data Index. décimale : 239 Fouille de données - Data mining Résumé : This book’s updated 2nd edition shows application architects, developers, and production engineers new to the Kafka open source streaming platform how to handle real-time data feeds. Additional chapters cover Kafka’s AdminClient API, new security features, and tooling changes. [D'après le résumé de l'éditeur] Note de contenu : Mise à jour 20/10/22. Mise à jour 09/02/23 En ligne : https://www.oreilly.com/library/view/kafka-the-definitive/9781492043072/ Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=165420 
Mathematics of data science : a computational approach to clustering and classification [texte imprimé] / Calvetti, Daniela ; Erkki Somersalo . - Philadelphie, PA : SIAM. Society for Industrial and Applied Mathematics, 2021 . - x-189 p.. - (Data science book series) .ISBN : 978-1-61197-636-6Langues : Anglais (eng)Descripteurs : Analyse des données , Analyse discriminante , Classification automatique , Données massives , Statistique computationnelle Tags : Principal component analysis Linear discriminant analysis K-means and k-medoids Non-negative matrix factorization Self-organizing maps Query matching Gray level co-occurrence matrices Support vector machine Classification and regression trees PageRank Random forests Learning vector quantifier Text mining Index. décimale : 219 Statistique descriptive multidimensionnelle Résumé : This textbook provides a solid mathematical basis for understanding popular data science algorithms for clustering and classification and shows that an in-depth understanding of the mathematics powering these algorithms gives insight into the underlying data. It presents a step-by-step derivation of these algorithms, outlining their implementation from scratch in a computationally sound way. [D'après le résumé de l'éditeur] Note de contenu : . Mise à jour 06/08/21. Mise à jour 23/12/21. Mise à jour 01/06/22. Mise à jour 21/10/22. Mise à jour 09/02/23 En ligne : https://my.siam.org/Store/Product/viewproduct/?ProductId=32863041 Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=165428 Noise filtering for big data analytics
Noise filtering for big data analytics [texte imprimé] / Souvik Bhattacharyya, Éditeur scientifique ; Koushik Ghosh, Éditeur scientifique . - Berlin ; New York : Walter De Gruyter, 2022 . - 248 p. : ill., tabl. ; 25 cm. - (De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences; Volume 12) .ISBN : 978-3-11-069709-4IndexLangues : Anglais (eng)Descripteurs : Analyse des données , Big data , Filtrage , Lissage Index. décimale : 239 Fouille de données - Data mining Résumé : This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model. Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information. This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it. [Résumé éditeur] Note de contenu : . Mise à jour 09/02/23 En ligne : https://www.degruyter.com/document/doi/10.1515/9783110697216/html Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=171567 
Object oriented data analysis [texte imprimé] / Ian L. Dryden ; James Stephen Marron, . - Boca Raton, FL ; Londres : Chapman and Hall/CRC Press, 2022 . - 464 p. : fig. ; 24 cm. - (Chapman & Hall/CRC Monographs on Statistics and Applied Probability, ISSN 0960-6696; 169) .ISBN : 978-0-8153-9282-8IndexLangues : Anglais (eng)Descripteurs : Analyse des données , Classification , Fouille de données , Inférence statistiqueEnsemble de méthodes permettant de tirer des conclusions fiables à partir de données d'échantillons statistiques , Robustesse Index. décimale : 232 Analyse des données Résumé : Object Oriented Data Analysis is a framework that facilitates inter-disciplinary research through new terminology for discussing the often many possible approaches to the analysis of complex data. Such data are naturally arising in a wide variety of areas. This book aims to provide ways of thinking that enable the making of sensible choices. [Résumé éditeur] Note de contenu : Mise à jour 18/10/22. Mise à jour 09/02/23 En ligne : https://www.routledge.com/Object-Oriented-Data-Analysis/Marron-Dryden/p/book/978 [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=165636 Presenting scientific data in R
Presenting scientific data in R : creating effective graphs and figures [texte imprimé] / Rosalind K. Humphreys ; Graeme D. Ruxton . - Oxford (GBR) ; New York ; Paris : OUP. Oxford University Press, 2022 . - 208 p. ; 25 cm. - (Oxford Biology Primers) .ISBN : 978-0-19-887047-0IndexLangues : Anglais (eng)Descripteurs : Logiciel statistique R , Représentation graphique Tags : Qualitative data Histograms Boxplots Scatterplots Pie charts Tables Index. décimale : 205 Graphique - Cartographie Résumé : It offers valuable and widely applicable advice on how to choose the most appropriate type of graph for different types of data, and guides readers from the basics of plotting clear figures to producing polished and effective visuals, illustrating the core concepts and features of excellent graphing. This primer uses simple and engaging biology-based example data sets to take readers from the essential aspects of basic plots to more advanced graphing techniques and details. [D'après le résumé de l'éditeur] Note de contenu : . Mise à jour 09/02/23 En ligne : https://global.oup.com/academic/product/presenting-scientific-data-in-r-97801988 [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=171580 Python for geospatial data analysis
Python for geospatial data analysis : theory, tools and practice for location intelligence [texte imprimé] / Bonny P. McClain . - Sebastopol, CA ; Cambridge (GBR) : O'Reilly, 2022 . - 200 p. ; 24 cm.ISBN : 978-1-09-810479-5IndexLangues : Anglais (eng)Descripteurs : Analyse des données , Données massives , Entrepôt de données , Géostatistique Tags : Python Index. décimale : 258 Géostatistique - Environnemétrie Résumé : In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, data scientists, business analysts, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions. The author demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python. [D'après le résumé de l'éditeur] Note de contenu : Mise à jour 20/10/22. Mise à jour 09/02/23 En ligne : https://www.oreilly.com/library/view/python-for-geospatial/9781098104788/ Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=171509 
Secure data science : integrating cyber security and data science [texte imprimé] / Bhavani M. Thuraisingham ; Murat Kantarcioglu ; Latifur Khan . - Boca Raton, FL ; Londres : Chapman and Hall/CRC Press, 2022 . - 456 p. : ill. ; 25 cm.ISBN : 978-0-367-53410-3Langues : Anglais (eng)Descripteurs : Apprentissage automatique , Données massives , Fouille de données , Sécurité informatique Tags : Data mining Computer security Science des données sécurisées Cybersécurité Science des données Analyse des logiciels malveillants Détection des menaces internes Confidentialité des services de mégadonnées Confidentialité du cloud computing Index. décimale : 239 Fouille de données - Data mining Résumé : After an overview of security and privacy for big data services as well as cloud computing, this book describes applications of data science for cyber security applications. It also discusses such applications of data science as malware analysis and insider threat detection. Then this book addresses trends in adversarial machine learning and provides solutions to the attacks on the data science techniques. In particular, it discusses some emerging trends in carrying out trustworthy analytics so that the analytics techniques can be secured against malicious attacks. Then it focuses on the privacy threats due to the collection of massive amounts of data and potential solutions. Following a discussion on the integration of services computing, including cloud-based services for secure data science, it looks at applications of secure data science to information sharing and social media. This book is a useful resource for researchers, software developers, educators, and managers who want to understand both the high level concepts and the technical details on the design and implementation of secure data science-based systems. It can also be used as a reference book for a graduate course in secure data science. Furthermore, this book provides numerous references that would be helpful for the reader to get more details about secure data science. [D'après le résumé de l'éditeur] Note de contenu : . Mise à jour 09/02/23 En ligne : https://www.routledge.com/Secure-Data-Science-Integrating-Cyber-Security-and-Dat [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=171615 
Spatial analysis [texte imprimé] / Kanti V. Mardia (1935-....) ; John T. Kent . - Chichester (GBR) ; Hoboken, NJ : John Wiley & Sons, 2022 . - 426 p.. - (Wiley series in probability and statistics, ISSN 1940-6517) .ISBN : 978-0-471-63205-4Index Langues originales : Anglais (eng)Descripteurs : Analyse spatiale , Variable aléatoire Index. décimale : 258 Géostatistique - Environnemétrie Résumé : In this book, two distinguished authors deliver a practical and insightful exploration of the statistical investigation of the interdependence of random variables as a function of their spatial proximity. The book expertly blends theory and application, offering numerous worked examples and exercises at the end of each chapter. Increasingly relevant to fields as diverse as epidemiology, geography, geology, image analysis, and machine learning, spatial statistics is becoming more important to a wide range of specialists and professionals. [Résumé éditeur] Note de contenu : . Mise à jour 10/06/22. Mise à jour 21/10/22. Mise à jour 09/02/23 Note sur les bibliographies ou index : Bibliogr. p. 497-501. Index En ligne : https://www.wiley.com/en-gb/Spatial+Analysis-p-9780471632054 Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=170981 
Spatiotemporal analytics [texte imprimé] / Jay Lee . - Boca Raton, FL ; Londres : Chapman and Hall/CRC Press, 2023 . - 256 p. : ill. ; 24 cm.ISBN : 978-1-03-230305-5IndexLangues : Anglais (eng)Descripteurs : Analyse spatiale Tags : Analyse spatio-temporelle Index. décimale : 258 Géostatistique - Environnemétrie Résumé : This book introduces readers to spatiotemporal analytics that are extended from spatial statistics. Spatiotemporal analytics help analysts to quantitatively recognize and evaluate the spatial patterns and their temporal trends of a set of geographic events or objects. Spatiotemporal analyses are very important in geography, environmental sciences, economy, and many other domains. This book explains with very simple terms the concepts of spatiotemporal data and statistics, theories, and methods used. [Résumé éditeur] Note de contenu : . Mise à jour 09/02/23 En ligne : https://www.routledge.com/Spatiotemporal-Analytics/Lee/p/book/9781032303055 Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=173090 Statistics and data visualization using R
Statistics and data visualization using R : the art and practice of data analysis [texte imprimé] / David S. Brown . - Thousand Oaks, CA ; Londres : SAGE Publications, 2021 . - 616 p. ; 26 cm.ISBN : 978-1-5443-3386-1IndexLangues : Anglais (eng)Descripteurs : Analyse des données , Exploration de données , Intervalle de confiance , Logiciel statistique R , Probabilités (Théorie) , Régression logistique , Régression multiple , Test d'hypothèses , Traitement des données Tags : Création de graphiques Visualisation de données Index. décimale : 239 Fouille de données - Data mining Résumé : Designed to introduce students to quantitative methods in a way that can be applied to all kinds of data in all kinds of situations, Statistics and Data Visualization Using R: The Art and Practice of Data Analysis by David S. Brown teaches students statistics through charts, graphs, and displays of data that help students develop intuition around statistics as well as data visualization skills. [D'après le résumé de l'éditeur] Note de contenu : Mise à jour 08/02/23 En ligne : https://uk.sagepub.com/en-gb/eur/statistics-and-data-visualization-using-r/book2 [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=165550 Statistiques et traitement des données
Statistiques et traitement des données : du recueil à l'interprétation [texte imprimé] / Léo Gerville-Réache . - Paris : Ellipses, 2022 . - 224 p. : ill. ; 24 cm. - (Objectif STAPS, ISSN 2497-434X) .ISBN : 978-2-340-07495-8STAPS = Sciences et Techniques des Activités Physiques et Sportives. - La couverture porte en plus : "L'essentiel à connaitre", "Douze problèmatiques traitées en profondeur". - Licence, MasterLangues : Français (fre)Descripteurs : Enquête statistique , Logiciel statistique R , Modélisation , Sports , Statistique descriptive , Statistique mathématique , Traitement des données Tags : Excel Statistiques sociales Index. décimale : 232 Analyse des données Résumé : Cet ouvrage propose une approche généraliste et spécifique de la statistique appliquée aux sciences du sport. Ce qu’il faut connaitre de la donnée à la comparaison, de l’enquête à l’expérimentation en passant par la modélisation est développé sans formalisme mathématique inutile. Avec la progressivité des problématiques et la possibilité de reproduire l’essentiel des analyses sous Excel et/ou R, cet ouvrage permet de développer ses connaissances et compétences en statistique et traitement des données. Il s'adresse aux étudiants de licences, masters et doctoratx STAPS, aux enseignants et enseignants-chercheurs en sciences du sport et aux data analystes traitant de données sportives. [Résumé éditeur] Note de contenu : . Mise à jour 09/02/23 En ligne : https://www.editions-ellipses.fr/accueil/14593-statistique-et-traitement-des-don [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=173226 The statistical analysis of doubly truncated data
The statistical analysis of doubly truncated data : with applications in R [texte imprimé] / Jacobo de Una-Alavarez, ; Rosa M. Crujeiras, ; Carla Moreira, . - Chichester (GBR) ; Hoboken, NJ : John Wiley & Sons, 2021 . - 192 p. ; 25 cm. - (Wiley series in probability and statistics, ISSN 1940-6517) .ISBN : 978-1-119-95137-7IndexLangues : Anglais (eng)Descripteurs : Analyse des données , Logiciel statistique R Tags : Analyse statistique Randomly truncated data Random double truncation Index. décimale : 232 Analyse des données Résumé : This book provides an up-to-date review of the existing methods to deal with randomly truncated data, with focus on the difficult problem of random double truncation. Doubly truncated data is introduced in a comprehensive way and explores the latest developments in this field. Illustrative examples with R code are provided along with real data examples from economy, and biomedical sciences to supplement the methods featured throughout the book. [Résumé de l'éditeur] Note de contenu : . Mise à jour 09/02/23 En ligne : https://www.wiley.com/en-gb/The+Statistical+Analysis+of+Doubly+Truncated+Data%3A [...] Permalink : https://genes.bibli.fr/index.php?lvl=notice_display&id=166660