Контакты/Проезд  Доставка и Оплата Помощь/Возврат
История
  +7(495) 980-12-10
  пн-пт: 10-18 сб,вс: 11-18
  shop@logobook.ru
   
    Поиск книг                    Поиск по списку ISBN Расширенный поиск    
Найти
  Зарубежные издательства Российские издательства  
Авторы | Каталог книг | Издательства | Новинки | Учебная литература | Акции | Хиты | |
 

Machine Conversations, Yorick Wilks


Варианты приобретения
Цена: 25149.00р.
Кол-во:
Наличие: Поставка под заказ.  Есть в наличии на складе поставщика.
Склад Америка: Есть  
При оформлении заказа до: 2025-09-15
Ориентировочная дата поставки: Октябрь
При условии наличия книги у поставщика.

Добавить в корзину
в Мои желания

Автор: Yorick Wilks
Название:  Machine Conversations
ISBN: 9780792385448
Издательство: Springer
Классификация:

ISBN-10: 0792385446
Обложка/Формат: Hardcover
Страницы: 221
Вес: 0.51 кг.
Дата издания: 31.07.1999
Серия: The Springer International Series in Engineering and Computer Science
Язык: English
Размер: 234 x 156 x 14
Основная тема: Computer Science
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: Describes various attempts to create practical and flexible machine conversation - ways of talking to computers in an unrestricted version of English or some other language. This book is for those interested in computational linguistics, cognitive science, natural language processing, artificial intelligence, and human computer interfaces.


Machine Learning

Автор: Kevin Murphy
Название: Machine Learning
ISBN: 0262018020 ISBN-13(EAN): 9780262018029
Издательство: MIT Press
Рейтинг:
Цена: 18622.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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.

Practical Machine Learning with H2O

Автор: Darren Cook
Название: Practical Machine Learning with H2O
ISBN: 149196460X ISBN-13(EAN): 9781491964606
Издательство: Wiley
Рейтинг:
Цена: 6334.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms.

Machine Learning

Автор: Marsland
Название: Machine Learning
ISBN: 1466583282 ISBN-13(EAN): 9781466583283
Издательство: Taylor&Francis
Рейтинг:
Цена: 12095.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

A Proven, Hands-On Approach for Students without a Strong Statistical Foundation

Since the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms. Unfortunately, computer science students without a strong statistical background often find it hard to get started in this area.

Remedying this deficiency, Machine Learning: An Algorithmic Perspective, Second Edition helps students understand the algorithms of machine learning. It puts them on a path toward mastering the relevant mathematics and statistics as well as the necessary programming and experimentation.

New to the Second Edition

  • Two new chapters on deep belief networks and Gaussian processes
  • Reorganization of the chapters to make a more natural flow of content
  • Revision of the support vector machine material, including a simple implementation for experiments
  • New material on random forests, the perceptron convergence theorem, accuracy methods, and conjugate gradient optimization for the multi-layer perceptron
  • Additional discussions of the Kalman and particle filters
  • Improved code, including better use of naming conventions in Python

Suitable for both an introductory one-semester course and more advanced courses, the text strongly encourages students to practice with the code. Each chapter includes detailed examples along with further reading and problems. All of the code used to create the examples is available on the author's website.

Machine Learning: The New AI

Автор: Alpaydin Ethem
Название: Machine Learning: The New AI
ISBN: 0262529513 ISBN-13(EAN): 9780262529518
Издательство: MIT Press
Рейтинг:
Цена: 2700.00 р.
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.

Machine Learning and Data Mining in Pattern Recognition

Автор: Petra Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319624156 ISBN-13(EAN): 9783319624150
Издательство: Springer
Рейтинг:
Цена: 9781.00 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 multi-media data types such as image mining, text mining, video mining, and Web mining.

Machine-learning Techniques in Economics

Автор: Atin Basuchoudhary; James T. Bang; Tinni Sen
Название: Machine-learning Techniques in Economics
ISBN: 3319690132 ISBN-13(EAN): 9783319690131
Издательство: Springer
Рейтинг:
Цена: 7685.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book develops a machine-learning framework for predicting economic growth. While machine learning itself is not a new idea, advances in computing technology combined with a dawning realization of its applicability to economic questions makes it a new tool for economists.

Machine Translation

Автор: F. Derek Wong; Deyi Xiong
Название: Machine Translation
ISBN: 9811071330 ISBN-13(EAN): 9789811071331
Издательство: Springer
Рейтинг:
Цена: 8384.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the refereed proceedings of the 13th China Workshop on Machine Translation, CWMT 2017, held in Dalian, China, in September 2017.
The 10 papers presented in this volume were carefully reviewed and selected from 26 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.

Machine Learning with R

Автор: Abhijit Ghatak
Название: Machine Learning with R
ISBN: 9811068070 ISBN-13(EAN): 9789811068072
Издательство: Springer
Рейтинг:
Цена: 10480.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book helps readers understand the mathematics of machine learning, and apply them in different situations. The book will be of interest to all researchers who intend to use R for machine learning, and those who are interested in the practical aspects of implementing learning algorithms for data analysis.

Quantum Machine Learning: What Quantum Computing Means to Data Mining

Автор: Wittek Peter
Название: Quantum Machine Learning: What Quantum Computing Means to Data Mining
ISBN: 0128100400 ISBN-13(EAN): 9780128100400
Издательство: Elsevier Science
Рейтинг:
Цена: 11789.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. . Quantum Machine Learning sets the scene for a deeper understanding of the subject for readers of different backgrounds. The author has carefully constructed a clear comparison of classical learning algorithms and their quantum counterparts, thus making differences in computational complexity and learning performance apparent. This book synthesizes of a broad array of research into a manageable and concise presentation, with practical examples and applications.

Bayesian Reasoning and Machine Learning

Автор: Barber
Название: Bayesian Reasoning and Machine Learning
ISBN: 0521518148 ISBN-13(EAN): 9780521518147
Издательство: Cambridge Academ
Рейтинг:
Цена: 11088.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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.

Machine Learning

Автор: Mitchell
Название: Machine Learning
ISBN: 0071154671 ISBN-13(EAN): 9780071154673
Издательство: McGraw-Hill
Рейтинг:
Цена: 10466.00 р.
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.

Non-Linguistic Analysis of Call Center Conversations

Автор: Sunil Kumar Kopparapu
Название: Non-Linguistic Analysis of Call Center Conversations
ISBN: 331900896X ISBN-13(EAN): 9783319008967
Издательство: Springer
Рейтинг:
Цена: 9141.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The book focuses on the part of the audio conversation not related to language such as speaking rate (in terms of number of syllables per unit time) and emotion centric features. The author analyzes "how" the conversation happens and not "what" the conversation is about by audio signal processing and analysis.


ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
   В Контакте     В Контакте Мед  Мобильная версия