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


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Цена: 27950.00р.
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Автор: Aboul Ella Hassanien, Ashraf Darwish   (Ашраф Дарвиш)
Название:  Machine Learning and Data Mining in Aerospace Technology
Перевод названия: Ашраф Дарвиш: Машинное обучение и интеллектуальный анализ данных в аэрокосмической технике
ISBN: 9783030202118
Издательство: Springer
Классификация:

ISBN-10: 3030202119
Обложка/Формат: Hardcover
Страницы: 232
Вес: 0.53 кг.
Дата издания: 16.07.2019
Серия: Studies in computational intelligence
Язык: English
Издание: 1st ed. 2020
Иллюстрации: 62 illustrations, color; 35 illustrations, black and white; viii, 232 p. 97 illus., 62 illus. in color.
Размер: 234 x 156 x 14
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites are the eagle eyes that allow us to view massive areas of the Earth simultaneously, and can gather more data, more quickly, than tools on the ground. Consequently, the development of intelligent health monitoring systems for artificial satellites - which can determine satellites current status and predict their failure based on telemetry data - is one of the most important current issues in aerospace engineering.

This book is divided into three parts, the first of which discusses central problems in the health monitoring of artificial satellites, including tensor-based anomaly detection for satellite telemetry data and machine learning in satellite monitoring, as well as the design, implementation, and validation of satellite simulators. The second part addresses telemetry data analytics and mining problems, while the last part focuses on security issues in telemetry data.




Computer Age Statistical Inference

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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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.

An Introduction to Machine Learning

Автор: Miroslav Kubat
Название: An Introduction to Machine Learning
ISBN: 3319348868 ISBN-13(EAN): 9783319348865
Издательство: Springer
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Цена: 6986.00 р.
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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.

Principles and Theory for Data Mining and Machine Learning

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
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Цена: 21661.00 р.
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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.

Machine Learning and Data Mining in Pattern Recognition

Автор: Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319419196 ISBN-13(EAN): 9783319419190
Издательство: Springer
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Цена: 13416.00 р.
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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.

Machine Learning and Data Mining in Pattern Recognition

Автор: Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319961357 ISBN-13(EAN): 9783319961354
Издательство: Springer
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Цена: 6986.00 р.
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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.

Machine Learning and Data Mining in Pattern Recognition

Автор: Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319961322 ISBN-13(EAN): 9783319961323
Издательство: Springer
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Цена: 10340.00 р.
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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.

Machine Learning for Beginners 2019: The Ultimate Guide to Artificial Intelligence, Neural Networks, and Predictive Modelling (Data Mining Algorithms

Автор: Henderson Matt
Название: Machine Learning for Beginners 2019: The Ultimate Guide to Artificial Intelligence, Neural Networks, and Predictive Modelling (Data Mining Algorithms
ISBN: 1999177037 ISBN-13(EAN): 9781999177034
Издательство: Неизвестно
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Цена: 6205.00 р.
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Описание:

Want to predict what your customers want to buy without them having to tell you? Want to accurately forecast sales trends for your marketing team better than any employee could ever do? Then keep reading.


You've heard it before. The rise of artificial intelligence and how it will soon replace human beings and take away our jobs. What exactly is it capable of and how does this impact me? The real question you should be asking yourself is how can I use this to my advantage? How can I use machine learning to benefit my business and surpass my business goals? This book has the answer.

Designed for the tech novice, this book will break down the fundamentals of machine learning and what it truly means. You will learn to leverage neural networks, predictive modelling, and data mining algorithms, illustrated with real-world applications for finance, business and marketing.

Machine learning isn't just for scientists or engineers anymore. It's become accessible to anyone, and you can discover it's benefits for your business.

In Machine Learning for Beginners 2019, we will reveal:

✅ The fundamentals of machine learning.

✅ Each of the buzzwords defined

✅ 20 real-world applications of machine learning.

✅ How to predict when a customer is about to churn (and prevent it from happening).

✅ How to "upsell" to your customers and close more sales.

✅ How to deal with missing data or poor data.

✅ Where to find free datasets and libraries.

✅ Exactly which machine learning libraries you need.

✅ And much much more


I know you might be overwhelmed at this point, but I assure you this book has been designed for absolute beginners. Everything is in plain English. There is no code, so no coding experience is required. You won't walk away a machine learning god, but you will walk away with key strategies you can implement right away to improve your business.

���� If you are ready to start making big changes to your business, scroll up and click buy. ����

Principles and Theory for Data Mining and Machine Learning

Автор: Clarke
Название: Principles and Theory for Data Mining and Machine Learning
ISBN: 0387981349 ISBN-13(EAN): 9780387981345
Издательство: Springer
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Цена: 27950.00 р.
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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

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

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
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Цена: 9781.00 р.
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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.

Machine Learning for Protein Subcellular Localization Prediction

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: 13008.00 р.
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.

Statistics, data mining, and machine learning in astronomy :

Автор: Ivezic?, Z?eljko,
Название: Statistics, data mining, and machine learning in astronomy :
ISBN: 0691198306 ISBN-13(EAN): 9780691198309
Издательство: Wiley
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Цена: 12355.00 р.
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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

Machine Learning and Data Mining in Pattern Recognition

Автор: Petra Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319210238 ISBN-13(EAN): 9783319210230
Издательство: Springer
Рейтинг:
Цена: 8944.00 р.
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.


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