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An Introduction to Machine Learning, Kubat Miroslav


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Цена: 8384.00р.
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При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября

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Автор: Kubat Miroslav
Название:  An Introduction to Machine Learning
ISBN: 9783030819347
Издательство: Springer
Классификация:




ISBN-10: 3030819345
Обложка/Формат: Hardcover
Страницы: 432
Вес: 0.84 кг.
Дата издания: 18.10.2021
Язык: English
Издание: 3rd ed. 2021
Иллюстрации: 5 illustrations, color; 109 illustrations, black and white; xviii, 454 p. 114 illus., 5 illus. in color.
Размер: 23.39 x 15.60 x 2.69 cm
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Julie Winkle Giulioni offers you a new approach for developing your employees` careers and helping them thrive in a company when promotions are not readily available. You will gain a new perspective on career development and practical tools through an easy-to-apply framework of seven alternative dimensions of development that will engage your employees.


Introduction to algorithms  3 ed.

Автор: Cormen, Thomas H., E
Название: Introduction to algorithms 3 ed.
ISBN: 0262033844 ISBN-13(EAN): 9780262033848
Издательство: MIT Press
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Цена: 27588.00 р.
Наличие на складе: Нет в наличии.

Описание: A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-base flow.

Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.

Автор: Witten, Ian H.
Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.
ISBN: 0128042915 ISBN-13(EAN): 9780128042915
Издательство: Elsevier Science
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Цена: 9262.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.

Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.

Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.

It contains

  • Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
  • Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
  • Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.

  • Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
  • Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
  • Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
  • Includes open-access online courses that introduce practical applications of the material in the book
A Brief Introduction to Continuous Evolutionary Optimization

Автор: Oliver Kramer
Название: A Brief Introduction to Continuous Evolutionary Optimization
ISBN: 3319034219 ISBN-13(EAN): 9783319034218
Издательство: Springer
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Цена: 9141.00 р.
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Описание: This book introduces heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. It presents heuristic extensions that allow optimization in constrained, multimodal and multi-objective solution spaces.

Introduction to multiagent systems

Автор: Wooldridge, Michael
Название: Introduction to multiagent systems
ISBN: 0470519460 ISBN-13(EAN): 9780470519462
Издательство: Wiley
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Цена: 9021.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The eagerly anticipated updated resource on one of the most important areas of research and development: multi-agent systems Multi-agent systems allow many intelligent agents to interact with each other, and this field of study has advanced at a rapid pace since the publication of the first edition of this book, which was nearly a decade ago.

An Introduction to IoT Analytics

Автор: Perros, Harry G.
Название: An Introduction to IoT Analytics
ISBN: 0367686317 ISBN-13(EAN): 9780367686314
Издательство: Taylor&Francis
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Цена: 7348.00 р.
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Описание: This book covers techniques that can be used to analyze data from IoT sensors and also addresses questions regarding the performance of an IoT system. It strikes a balance between practice and theory so that one can learn how to apply these tools in practice with a good understanding of their inner workings.

Machine Learning for Beginners: An Introduction to Artificial Intelligence and Machine Learning

Автор: Slavio John
Название: Machine Learning for Beginners: An Introduction to Artificial Intelligence and Machine Learning
ISBN: 1922300152 ISBN-13(EAN): 9781922300157
Издательство: Неизвестно
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Цена: 4228.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

So you've heard a lot about AI and Machine learning. But what does it actually mean?
This book could be the answer you're looking for...

This book is an introduction to basic machine learning and artificial intelligence. It gives you a list of applications, and also a few examples of the different types of machine learning.

Here's What You'll Learn in this Book:

  • Introduction to Machine Learning
  • Different Applications of Machine Learning
  • Introduction to Statistics for Machine Learning
  • Supervised Learning
  • Unsupervised Learning
  • Reinforced Learning
  • Conclusion
An Introduction to Machine Learning

Автор: Rebala Gopinath, Ravi Ajay, Churiwala Sanjay
Название: An Introduction to Machine Learning
ISBN: 3030157318 ISBN-13(EAN): 9783030157319
Издательство: Springer
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Цена: 18167.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

An Introduction to Machine Learning

Автор: Gopinath Rebala; Ajay Ravi; Sanjay Churiwala
Название: An Introduction to Machine Learning
ISBN: 3030157288 ISBN-13(EAN): 9783030157289
Издательство: Springer
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Цена: 15372.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Just like electricity, Machine Learning will revolutionize our life in many ways – some of which are not even conceivable today. This book provides a thorough conceptual understanding of Machine Learning techniques and algorithms. Many of the mathematical concepts are explained in an intuitive manner. The book starts with an overview of machine learning and the underlying Mathematical and Statistical concepts before moving onto machine learning topics. It gradually builds up the depth, covering many of the present day machine learning algorithms, ending in Deep Learning and Reinforcement Learning algorithms. The book also covers some of the popular Machine Learning applications. The material in this book is agnostic to any specific programming language or hardware so that readers can try these concepts on whichever platforms they are already familiar with. Offers a comprehensive introduction to Machine Learning, while not assuming any prior knowledge of the topic;Provides a complete overview of available techniques and algorithms in conceptual terms, covering various application domains of machine learning;Not tied to any specific software language or hardware implementation.

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.
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.

Introduction to Machine Learning with R: Rigorous Mathematical Analysis

Автор: Burger Scott V.
Название: Introduction to Machine Learning with R: Rigorous Mathematical Analysis
ISBN: 1491976446 ISBN-13(EAN): 9781491976449
Издательство: Wiley
Рейтинг:
Цена: 7126.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles.

An Introduction to Machine Learning

Автор: Miroslav Kubat
Название: An Introduction to Machine Learning
ISBN: 3319876694 ISBN-13(EAN): 9783319876696
Издательство: Springer
Рейтинг:
Цена: 6986.00 р.
Наличие на складе: Поставка под заказ.

Описание: This textbook presents fundamental machine learning concepts in an easy to understand manner by providing practical advice, using straightforward examples, and offering engaging discussions of relevant applications.

A Hands-On Introduction to Data Science

Автор: Chirag Shah
Название: A Hands-On Introduction to Data Science
ISBN: 1108472443 ISBN-13(EAN): 9781108472449
Издательство: Cambridge Academ
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Цена: 7286.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: A practical introduction to data science with a low barrier entry, this textbook is well-suited to students from a range of disciplines. Assuming no prior knowledge of the subject, the hands-on exercises and real-life application of popular data science tools are accessible even to students without a strong technical background.


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