Genetic Algorithms for Machine Learning, John J. Grefenstette

Автор: Kevin Murphy
Название: Machine Learning
ISBN: 0262018020 ISBN-13(EAN): 9780262018029
Издательство: MIT Press
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Цена: 124150.00 T
Наличие на складе: Невозможна поставка.
Описание:

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.

The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package -- PMTK (probabilistic modeling toolkit) -- that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Автор: Mohammed
Название: Machine Learning,Algorithms And App
ISBN: 1498705383 ISBN-13(EAN): 9781498705387
Издательство: Taylor&Francis
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Цена: 84710.00 T
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Описание: Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the subject material. This book provides a more practical approach by explaining the concepts of machine learning algorithms and describing the areas of application for each algorithm, using simple practical examples to demonstrate each algorithm and showing how different issues related to these algorithms are applied.

Автор: Shan Suthaharan
Название: Machine Learning Models and Algorithms for Big Data Classification
ISBN: 148997640X ISBN-13(EAN): 9781489976406
Издательство: Springer
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Цена: 121110.00 T
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Описание: This book presents machine learning models and algorithms to address big data classification problems. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The third part presents the topics required to understand and select machine learning techniques to classify big data.

Автор: Barber
Название: Bayesian Reasoning and Machine Learning
ISBN: 0521518148 ISBN-13(EAN): 9780521518147
Издательство: Cambridge Academ
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Цена: 73920.00 T
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Описание: This practical introduction for final-year undergraduate and graduate students is ideally suited to computer scientists without a background in calculus and linear algebra. Numerous examples and exercises are provided. Additional resources available online and in the comprehensive software package include computer code, demos and teaching materials for instructors.

Автор: Buduma Nikhil
Название: Fundamentals of Deep Learning: Designing Next-Generation Artificial Intelligence Algorithms
ISBN: 1491925612 ISBN-13(EAN): 9781491925614
Издательство: Wiley
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Цена: 36950.00 T
Наличие на складе: Невозможна поставка.
Описание: In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. If you`re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started.

Автор: Bekkerman
Название: Scaling up Machine Learning
ISBN: 0521192242 ISBN-13(EAN): 9780521192248
Издательство: Cambridge Academ
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Цена: 98210.00 T
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Описание: In many practical situations it is impossible to run existing machine learning methods on a single computer, because either the data is too large or the speed and throughput requirements are too demanding. Researchers and practitioners will find here a variety of machine learning methods developed specifically for parallel or distributed systems, covering algorithms, platforms and applications.

Автор: Mitchell
Название: Machine Learning
ISBN: 0071154671 ISBN-13(EAN): 9780071154673
Издательство: McGraw-Hill
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Цена: 69770.00 T
Наличие на складе: Поставка под заказ.
Описание: Covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. This book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.

Автор: Alpaydin Ethem
Название: Machine Learning: The New AI
ISBN: 0262529513 ISBN-13(EAN): 9780262529518
Издательство: MIT Press
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Цена: 18000.00 T
Наличие на складе: Нет в наличии.
Описание:

A concise overview of machine learning -- computer programs that learn from data -- which underlies applications that include recommendation systems, face recognition, and driverless cars.

Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition -- as well as some we don't yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn the algorithms for the tasks automatically from data. As computing devices grow more ubiquitous, a larger part of our lives and work is recorded digitally, and as "Big Data" has gotten bigger, the theory of machine learning -- the foundation of efforts to process that data into knowledge -- has also advanced. In this book, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications.

Alpaydin offers an account of how digital technology advanced from number-crunching mainframes to mobile devices, putting today's machine learning boom in context. He describes the basics of machine learning and some applications; the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances, with such applications as customer segmentation and learning recommendations; and reinforcement learning, when an autonomous agent learns act so as to maximize reward and minimize penalty. Alpaydin then considers some future directions for machine learning and the new field of "data science," and discusses the ethical and legal implications for data privacy and security.

Автор: Japkowicz
Название: Evaluating Learning Algorithms
ISBN: 1107653118 ISBN-13(EAN): 9781107653115
Издательство: Cambridge Academ
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Цена: 59130.00 T
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Описание: This book gives a solid basis for conducting performance evaluations of learning algorithms in practical settings with an emphasis on classification algorithms. The authors describe several techniques designed to deal with performance measures and methods, error estimation or re-sampling techniques, statistical significance testing, data set selection and evaluation benchmark design.

Автор: M. Emre Celebi; Kemal Aydin
Название: Unsupervised Learning Algorithms
ISBN: 3319242091 ISBN-13(EAN): 9783319242095
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity among researchers and practitioners.

Автор: Conway Drew, White John Myles
Название: Machine Learning for Hackers
ISBN: 1449303714 ISBN-13(EAN): 9781449303716
Издательство: Wiley
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Цена: 42230.00 T
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Описание: Now that storage and collection technologies are cheaper and more precise, methods for extracting relevant information from large datasets is within the reach any experienced programmer willing to crunch data.

Автор: Fuchen Sun; Kar-Ann Toh; Manuel Grana Romay; Kezhi
Название: Extreme Learning Machines 2013: Algorithms and Applications
ISBN: 331904740X ISBN-13(EAN): 9783319047409
Издательство: Springer
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Цена: 130610.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods.