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Data Science Par La Pratique


Author : Joel Grus
language : fr
Publisher: Editions Eyrolles
Release Date : 2017-05-11


PDF Download Data Science Par La Pratique Books For free written by Joel Grus and has been published by Editions Eyrolles this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-11 with Analyse des données categories.


Un ouvrage de référence pour les (futurs) data scientists. Les bibliothèques, les frameworks, les modules et les boîtes à outils sont parfaits pour faire de la data science. Ils sont aussi un bon moyen de plonger dans la discipline sans comprendre la data science. Dans cet ouvrage, vous apprendrez comment fonctionnent les outils et algorithmes les plus fondamentaux de la data science, en les réalisant à partir de zéro. Si vous êtes fort en maths et que vous connaissez la programmation, l'auteur, Joel Grus, vous aidera à vous familiariser avec les maths et les statistiques qui sont au coeur de la data science et à acquérir les compétences informatiques indispensables pour démarrer comme data scientist. La profusion des données d'aujourd'hui contient les réponses aux questions que personne n'a encore pensé à poser. Ce livre vous enseigne comment obtenir ces réponses. Suivez un cours accéléré de Python. Apprenez les fondamentaux de l'algèbre linéaire, des statistiques et des probabilités, et comprenez comment et quand les utiliser en data science. Collectez, explorez, nettoyez, bricolez et manipulez les données. Plongez dans les bases de l'apprentissage automatique. Implémentez des modèles comme les k plus proches voisins, le Bayes naïf, les régressions linéaire ou logistique, les arbres de décision, les réseaux neuronaux et le clustering. Explorez les systèmes de recommandation, le traitement du langage naturel, l'analyse de réseau, MapReduce et les bases de données. A qui s'adresse cet ouvrage ? Aux développeurs, statisticiens, étudiants et chefs de projet ayant à résoudre des problèmes de data science. Aux data scientists, mais aussi à toute personne curieuse d'avoir une vue d'ensemble de l'état de l'art de ce métier du futur.

Statistical Learning And Data Science


Author : Mireille Gettler Summa
language : en
Publisher: CRC Press
Release Date : 2011-12-19


PDF Download Statistical Learning And Data Science Books For free written by Mireille Gettler Summa and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-19 with Business & Economics categories.


Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream. Unsupervised data analysis, including cluster analysis, factor analysis, and low dimensionality mapping methods continually being updated, have reached new heights of achievement in the incredibly rich data world that we inhabit. Statistical Learning and Data Science is a work of reference in the rapidly evolving context of converging methodologies. It gathers contributions from some of the foundational thinkers in the different fields of data analysis to the major theoretical results in the domain. On the methodological front, the volume includes conformal prediction and frameworks for assessing confidence in outputs, together with attendant risk. It illustrates a wide range of applications, including semantics, credit risk, energy production, genomics, and ecology. The book also addresses issues of origin and evolutions in the unsupervised data analysis arena, and presents some approaches for time series, symbolic data, and functional data. Over the history of multidimensional data analysis, more and more complex data have become available for processing. Supervised machine learning, semi-supervised analysis approaches, and unsupervised data analysis, provide great capability for addressing the digital data deluge. Exploring the foundations and recent breakthroughs in the field, Statistical Learning and Data Science demonstrates how data analysis can improve personal and collective health and the well-being of our social, business, and physical environments.

Frontiers In Data Science


Author : Matthias Dehmer
language : en
Publisher: CRC Press
Release Date : 2017-10-16


PDF Download Frontiers In Data Science Books For free written by Matthias Dehmer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-16 with Computers categories.


Frontiers in Data Science deals with philosophical and practical results in Data Science. A broad definition of Data Science describes the process of analyzing data to transform data into insights. This also involves asking philosophical, legal and social questions in the context of data generation and analysis. In fact, Big Data also belongs to this universe as it comprises data gathering, data fusion and analysis when it comes to manage big data sets. A major goal of this book is to understand data science as a new scientific discipline rather than the practical aspects of data analysis alone.

Journal D Agriculture Pratique


Author :
language : fr
Publisher:
Release Date : 1873


PDF Download Journal D Agriculture Pratique Books For free written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1873 with categories.




Advances In Data Science And Classification


Author : International Federation of Classification Societies. Conference
language : en
Publisher: Springer Verlag
Release Date : 1998


PDF Download Advances In Data Science And Classification Books For free written by International Federation of Classification Societies. Conference and has been published by Springer Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Business & Economics categories.


The book provides new developments in classification and data analysis, and presents new topics which are of central interest to modern statistics. In particular, these include classification theory, multivariate data analysis, multi-way data, proximity structure analysis, new software for classification and data analysis, and applications in social, economic, medical and other sciences. For many of these topics, this book provides a systematic state of the art written by top researchers in the world. This book will serve as a helpful introduction to the area of classification and data analysis for research workers and support the transfer of new advances in data science and classification to a wide range of applications.

Data Science Classification And Related Methods


Author : Chikio Hayashi
language : en
Publisher: Egully.com
Release Date : 1998


PDF Download Data Science Classification And Related Methods Books For free written by Chikio Hayashi and has been published by Egully.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Business & Economics categories.


This is the proceedings of the Fifth Conference of the International Federation of Classification Societies held in Kobe, Japan, on March 27-30, 1996: The astounding increase in computer usage over the past decade and the ever-increasing scope of global communication networks have ushered in the information age; however, human intelligence is required to make sense of this sea of data and to use it effectively. Consequently, the rapidly developing cross-disciplinary field of data science has come of age. This volume contains selected papers from the Fifth Conference of the International Federation of Classification Societies (IFCS-96), held in Kobe, Japan, in March 1996. A wide range of topics is covered, including theoretical and methodological advances relating to data gathering, classification and clustering, exploratory and multivariate data analysis, and knowledge seeking and discovery. A broad view of the state of the art is presented, making this an essential work not only for data analysts, mathematicians, and statisticians but also for researchers involved in data processing at all stages from data gathering to decision making.

La R Gression Pls


Author : Michel Tenenhaus
language : fr
Publisher: Editions TECHNIP
Release Date : 1998


PDF Download La R Gression Pls Books For free written by Michel Tenenhaus and has been published by Editions TECHNIP this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Least squares categories.


La régression PLS (Partial Least Squares) est une méthode d’analyse des données qui connaît de grands développements, principalement dans le domaine des industries chimiques, pétrolières et agro-alimentaires. Sur le plan théorique, l’ouvrage a trois objectifs : situer la régression PLS parmi les méthodes d’association et de prédiction en analyse des données ; décrire l’algorithme de régression PLS dans sa forme originale telle qu’elle est programmée dans des logiciels comme SIMCA ou The Unscrambler ; présenter en détail les principales propriétés mathématiques de la régression PLS. Sur le plan pratique, l’ouvrage illustre l’apport de la régression PLS en l’utilisant sur de nombreux exemples et décrit avec un maximum de détails les sorties du logiciel de référence (SIMCA) à partir de ces exemples. Ainsi, un utilisateur de la régression PLS trouve dans ce livre toute l’aide nécessaire pour une exploitation optimale des résultats. "Ce livre clair, agréable à lire, et dont la calligraphie est excellente constitue une remarquable synthèse sur les méthodes PLS et, de façon plus générale, sur les techniques de liaison entre deux ensembles de variables, avec un grand nombre de résultats nouveaux" (Revue de Statistique Appliquée, mars 1999). Table des matières : 1. Introduction. 2. Analyse canonique. 3. Analyse factorielle inter-batteries. 4. Analyse des redondances. 5. Approche SIMPLS. 6. Algorithme NIPALS. 7. Régression PLS univariée (PLS1). 8. Propriétés mathématiques de la régression PLS1. 9. Régression PLS multivariée (PLS2). 10. Applications de la régression PLS. 11. Analyse canonique PLS. 12. Traitement des données qualitatives. 13. Approche PLS. Bibliographie. Index.