Machine Learning and Data Mining in Aerospace Technology, Aboul Ella Hassanien, Ashraf Darwish

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
Рейтинг:
Цена: 60190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Автор: Clarke
Название: Principles and Theory for Data Mining and Machine Learning
ISBN: 0387981349 ISBN-13(EAN): 9780387981345
Издательство: Springer
Рейтинг:
Цена: 186330.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Extensive treatment of the most up-to-date topicsProvides the theory and concepts behind popular and emerging methodsRange of topics drawn from Statistics, Computer Science, and Electrical Engineering

Автор: Miroslav Kubat
Название: An Introduction to Machine Learning
ISBN: 3319348868 ISBN-13(EAN): 9783319348865
Издательство: Springer
Рейтинг:
Цена: 46570.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications.

Автор: Joseph J. S. Shang, Sergey T. Surzhikov
Название: Plasma Dynamics for Aerospace Engineering
ISBN: 110841897X ISBN-13(EAN): 9781108418973
Издательство: Cambridge Academ
Рейтинг:
Цена: 115110.00 T
Наличие на складе: Невозможна поставка.
Описание: This volume establishes the foundation and best practices for applying plasma dynamics to viable aerospace engineering plasma applications, offering a comprehensive review while providing directly usable problem-solving techniques. It bridges the gap between theoretical physics and modeling and simulation technique for studying plasma dynamics.

Автор: Clara Pizzuti; Marylyn D. Ritchie; Mario Giacobini
Название: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
ISBN: 3642011837 ISBN-13(EAN): 9783642011832
Издательство: Springer
Рейтинг:
Цена: 65210.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2009, held in Tubingen, Germany, in April 2009 co located with the Evo 2009 events. This book includes such topics as biomarker discovery, cell simulation and modeling, and ecological modeling.

Автор: Bertrand Clarke; Ernest Fokoue; Hao Helen Zhang
Название: Principles and Theory for Data Mining and Machine Learning
ISBN: 1461417074 ISBN-13(EAN): 9781461417071
Издательство: Springer
Рейтинг:
Цена: 144410.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a thorough introduction to the most important topics in data mining and machine learning. All the topics covered have undergone rapid development and this treatment offers a modern perspective emphasizing the most recent contributions.

Автор: Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319419196 ISBN-13(EAN): 9783319419190
Издательство: Springer
Рейтинг:
Цена: 89440.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.

Автор: Shibiao Wan,Man-Wai Mak
Название: Machine Learning for Protein Subcellular Localization Prediction
ISBN: 1501510487 ISBN-13(EAN): 9781501510489
Издательство: Walter de Gruyter
Цена: 86720.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Comprehensively covers protein subcellular localization from single-label prediction to multi-label prediction, and includes prediction strategies for virus, plant, and eukaryote species. Three machine learning tools are introduced to improve classification refinement, feature extraction, and dimensionality reduction.

Автор: Marcus A. Maloof
Название: Machine Learning and Data Mining for Computer Security
ISBN: 1849965447 ISBN-13(EAN): 9781849965446
Издательство: Springer
Рейтинг:
Цена: 130430.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: "Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security.

Автор: Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319961357 ISBN-13(EAN): 9783319961354
Издательство: Springer
Рейтинг:
Цена: 46570.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

Автор: Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319961322 ISBN-13(EAN): 9783319961323
Издательство: Springer
Рейтинг:
Цена: 68930.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

Автор: Ivezic?, Z?eljko,
Название: Statistics, data mining, and machine learning in astronomy :
ISBN: 0691198306 ISBN-13(EAN): 9780691198309
Издательство: Wiley
Рейтинг:
Цена: 86590.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Telescope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, engage with the different methods, and adapt them to their own fields of interest.

An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date.

• Fully revised and expanded
  
• Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets
  
• Features real-world data sets from astronomical surveys
  
• Uses a freely available Python codebase throughout
  
• Ideal for graduate students, advanced undergraduates, and working astronomers