Автор: Haines, Duane E. Название: Neuroanatomy Atlas in Clinical Context: Structures, Sections, Systems ISBN: 1975106687 ISBN-13(EAN): 9781975106683 Издательство: Lippincott Williams & Wilkins Рейтинг: Цена: 7875.00 р. 8750.00-10% Наличие на складе: Есть (1 шт.) Описание: Publisher's Note:"Neuroanatomy Atlas in Clinical Context is unique in integrating clinical information, correlations, and terminology with neuroanatomical concepts. It provides everything students need to not only master the anatomy of the central nervous system, but also understand its clinical relevance - ensuring preparedness for exams and clinical rotations. This authoritative approach, combined with salutary features such as full-color stained sections, extensive cranial nerve cross-referencing, and systems neurobiology coverage, sustains the legacy of this legendary teaching and learning tool.
Emphasizes neuroscience information, concepts, and images that collectively constitute a comprehensive, clinically oriented overview of systems neurobiologyOffers clear explanations, hundreds of review questions, and supplemental online resources that provide a sound anatomical basis for integrating neurobiological and clinical informationFeatures an abundance of updated and expanded clinical content throughout all chapters to reflect the latest neuroscience knowledgeExpands Clinical Syndromes of the Central Nervous System chapter to include a new section featuring Stroke SyndromesIntroduces numerous new MRI, CT, MRA, and MRV images, as well as updated full-color photographs and artwork, to bring the content to life like never beforeUses contemporary clinical and basic science terminology in its proper contextIntegrates detailed and richly illustrated coverage of neuroanatomy with neuroscience and clinical concepts, allowing students to understand the material's clinical context and relevanceOffers a wealth of neuroimaging examples, clinical photographs, and full-color artwork that vividly demonstrate how neuroanatomy presents in clinical practiceFeatures the masterful teaching of Duane E. Haines, PhD, FAAAS, FAAA, a widely respected and accomplished educator who has helped generations of students master neuroanatomy and neuroscienceeBook available for purchase. Fast, smart, and convenient, today's eBooks can transform learning.
These interactive, fully searchable tools offer 24/7 access on multiple devices, the ability to highlight and share notes, and more
Автор: Cormen, Thomas H., E Название: Introduction to algorithms 3 ed. ISBN: 0262033844 ISBN-13(EAN): 9780262033848 Издательство: MIT Press Рейтинг: 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.
Автор: Barab?si Название: Network Science ISBN: 1107076269 ISBN-13(EAN): 9781107076266 Издательство: Cambridge Academ Рейтинг: Цена: 7762.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Illustrated throughout in full colour, this pioneering textbook, spanning a wide range of disciplines from physics to the social sciences, is the only book needed for an introduction to network science. In modular format, with clear delineation between undergraduate and graduate material, its unique design is supported by extensive online resources.
Описание: This undergraduate textbook is a concise introduction to the basic toolbox of structures that allow efficient organization and retrieval of data, key algorithms for problems on graphs, and generic techniques for modeling, understanding, and solving algorithmic problems.
Автор: von zur Gathen Название: Modern Computer Algebra ISBN: 1107039037 ISBN-13(EAN): 9781107039032 Издательство: Cambridge Academ Рейтинг: Цена: 17582.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Designed to accompany one- or two-semester courses for advanced undergraduate or graduate students, this textbook is widely regarded as the `bible of computer algebra`. Its comprehensiveness and reliability also makes it an essential reference for professionals. This updated edition includes an overview of recent improvements in areas like primality testing.
Описание: If you last saw algorithms in a university course or at a job interview, you`re missing out on what they can do for your code. Learn different sorting and searching techniques, and when to use each.
Автор: Agarwal, Dr Basant, Baka, Benjamin Название: Hands-On Data Structures and Algorithms with Python 2 ed ISBN: 1788995570 ISBN-13(EAN): 9781788995573 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data structures help us to organize and align the data in a very efficient way. This book will surely help you to learn important and essential data structures through Python implementation for better understanding of the concepts.
A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.
Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.
After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.
Автор: Li, Fanzhang / Zhang, Li / Zhang, Zhao Название: Dynamic Fuzzy Machine Learning ISBN: 3110518708 ISBN-13(EAN): 9783110518702 Издательство: Walter de Gruyter Рейтинг: Цена: 22439.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.
Описание: Modern computing systems preserve all information in intricate binary codes. The evolution of systems and technologies that aid in this preservation process must be continually assessed to ensure that they are keeping up with the demands of society. Formation Methods, Models, and Hardware Implementation of Pseudorandom Number Generators: Emerging Research and Opportunities is a crucial scholarly resource that examines the current methodologies used in number generator construction, and how they pertain to the overall advancement of contemporary computer systems. Featuring coverage on relevant topics such as cellular automata theory, inhomogeneous cells, and sequence generators, this publication is ideal for software engineers, computer programmers, academicians, students, and researchers that are interested in staying abreast of innovative trends within the computer engineering field.
Описание: This handbook reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics.
Recommender systems are very popular nowadays, as both an academic research field and services provided by numerous companies for e-commerce, multimedia and Web content. Collaborative-based methods have been the focus of recommender systems research for more than two decades.
The unique feature of the compendium is the technical details of collaborative recommenders. The book chapters include algorithm implementations, elaborate on practical issues faced when deploying these algorithms in large-scale systems, describe various optimizations and decisions made, and list parameters of the algorithms.
This must-have title is a useful reference materials for researchers, IT professionals and those keen to incorporate recommendation technologies into their systems and services.
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