Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Christopher M. Bishop Название: Pattern Recognition and Machine Learning ISBN: 0387310738 ISBN-13(EAN): 9780387310732 Издательство: Springer Рейтинг: Цена: 79190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Автор: David J. C. MacKay Название: Information Theory, Inference and Learning Algorithms ISBN: 0521642981 ISBN-13(EAN): 9780521642989 Издательство: Cambridge Academ Рейтинг: Цена: 60190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This exciting and entertaining textbook is ideal for courses in information, communication and coding. It is an unparalleled entry point to these subjects for professionals working in areas as diverse as computational biology, data mining, financial engineering and machine learning.
Автор: Goodfellow Ian, Bengio Yoshua, Courville Aaron Название: Deep Learning ISBN: 0262035618 ISBN-13(EAN): 9780262035613 Издательство: MIT Press Рейтинг: Цена: 90290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
"Written by three experts in the field, Deep Learning is the only comprehensive book on the subject." -- Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.
The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.
Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Автор: Kevin Murphy Название: Machine Learning ISBN: 0262018020 ISBN-13(EAN): 9780262018029 Издательство: MIT Press Рейтинг: 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: Malley Название: Statistical Learning for Biomedical Data ISBN: 0521699096 ISBN-13(EAN): 9780521699099 Издательство: Cambridge Academ Рейтинг: Цена: 43290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Biomedical researchers need machine learning techniques to make predictions such as survival/death or response to treatment when data sets are large and complex. This highly motivating introduction to these machines explains underlying principles in nontechnical language, using many examples and figures, and connects these new methods to familiar techniques.
Автор: Dickey Название: Learning Latin the Ancient Way ISBN: 1107474574 ISBN-13(EAN): 9781107474574 Издательство: Cambridge Academ Рейтинг: Цена: 24290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: During the Roman empire Greek speakers learned Latin using textbooks that still offer special advantages: authentic and enjoyable vignettes about the ancient world, easy Latin composed by Romans, insight into ancient learning practices. This book makes the ancient Latin-learning materials available to modern students for the first time.
Автор: North American Cambridge Classics Project Название: Cambridge Latin Course Unit 1 ISBN: 0521004349 ISBN-13(EAN): 9780521004343 Издательство: Cambridge Academ Рейтинг: Цена: 41580.00 T Наличие на складе: Поставка под заказ. Описание: The North American Cambridge Latin Course is a well-established four-part Latin program whose approach combines a stimulating, continuous storyline with
grammatical development, work on derivatives, and cultural information. There is also a complete Language Information section, plus numerous color photographs illustrating life in the
Roman world. The Course has now been fully revised and updated in the light of feedback from user schools, and includes the very best in new research.
The Fourth Edition
continues to offer teachers and students alike a stimulating, reading-based approach to the study of Latin.
Автор: Archibald Название: Learning Latin and Greek from Antiquity to the Present ISBN: 1107051649 ISBN-13(EAN): 9781107051645 Издательство: Cambridge Academ Рейтинг: Цена: 95040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume provides a unique overview of the broad historical, geographical and social range of Latin and Greek as second languages. Elucidates the techniques of Latin and Greek instruction across time and place, and the contrasting socio-political circumstances that contributed to and resulted from this remarkably enduring field of study.
Автор: Buduma Nikhil Название: Fundamentals of Deep Learning: Designing Next-Generation Artificial Intelligence Algorithms ISBN: 1491925612 ISBN-13(EAN): 9781491925614 Издательство: Wiley Рейтинг: 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: Barber Название: Bayesian Reasoning and Machine Learning ISBN: 0521518148 ISBN-13(EAN): 9780521518147 Издательство: Cambridge Academ Рейтинг: Цена: 73920.00 T 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.
Автор: Cambridge School Classics Project Название: Cambridge Latin Course 2 ISBN: 0521644682 ISBN-13(EAN): 9780521644686 Издательство: Cambridge Academ Рейтинг: Цена: 29360.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The leading Latin course worldwide
Казахстан, 010000 г. Астана, проспект Туран 43/5, НП2 (офис 2) ТОО "Логобук" Тел:+7 707 857-29-98 ,+7(7172) 65-23-70 www.logobook.kz
