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Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence, Kiran Pachlasiya


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Цена: 239310.00T
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Склад Америка: 169 шт.  
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Автор: Kiran Pachlasiya
Название:  Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence
ISBN: 9781668439425
Издательство: Mare Nostrum (Eurospan)
Классификация:


ISBN-10: 1668439425
Обложка/Формат: Hardback
Страницы: 325
Вес: 0.33 кг.
Дата издания: 30.05.2022
Серия: E-book collection - copyright 2022
Язык: English
Размер: 279 x 216
Читательская аудитория: Professional and scholarly
Ключевые слова: Computer security,Information technology: general issues,Pattern recognition, COMPUTERS / Optical Data Processing,COMPUTERS / Security / General
Рейтинг:
Поставляется из: Англии
Описание: Discusses cyberattacks, security, and safety measures to protect data and presents the shortcomings faced by researchers and practitioners due to the unavailability of information about the Dark Web. Attacker techniques in these Dark Web environments are highlighted, along with intrusion detection practices and crawling of hidden content.

Linear Algebra and Learning from Data

Автор: Strang Gilbert
Название: Linear Algebra and Learning from Data
ISBN: 0692196382 ISBN-13(EAN): 9780692196380
Издательство: Cambridge Academ
Рейтинг:
Цена: 66520.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.

Mathematics for Machine Learning

Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong
Название: Mathematics for Machine Learning
ISBN: 110845514X ISBN-13(EAN): 9781108455145
Издательство: Cambridge Academ
Рейтинг:
Цена: 42230.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.

Pattern Recognition and Machine Learning

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.

Noise Filtering for Big Data Analytics

Автор: Koushik Ghosh, Souvik Bhattacharyya
Название: Noise Filtering for Big Data Analytics
ISBN: 3110697092 ISBN-13(EAN): 9783110697094
Издательство: Walter de Gruyter
Рейтинг:
Цена: 173490.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model.

Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information.

This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.


Data structures based on linear relations

Автор: Xingni Zhou, Zhiyuan Ren, Yanzhuo Ma, Kai Fan, Ji Xiang
Название: Data structures based on linear relations
ISBN: 3110595575 ISBN-13(EAN): 9783110595574
Издательство: Walter de Gruyter
Цена: 80520.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Data structures is a key course for computer science and related majors. This book presents a variety of practical or engineering cases and derives abstract concepts from concrete problems. Besides basic concepts and analysis methods, it introduces basic data types such as sequential list, tree as well as graph. This book can be used as an undergraduate textbook, as a training textbook or a self-study textbook for engineers.


Noise Filtering for Big Data Analytics

Автор: Koushik Ghosh, Souvik Bhattacharyya
Название: Noise Filtering for Big Data Analytics
ISBN: 3110697262 ISBN-13(EAN): 9783110697261
Издательство: Walter de Gruyter
Рейтинг:
Цена: 172320.00 T
Наличие на складе: Нет в наличии.
Описание:

This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model. Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information. This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.


Автор: Ji Xiang, Kai Fan, Xingni Zhou, Yanzhuo Ma, zhiyuan Ren
Название: [Set Data Structures and Algorithms Analysis, Vol 1+2]
ISBN: 311068165X ISBN-13(EAN): 9783110681659
Издательство: Walter de Gruyter
Рейтинг:
Цена: 128870.00 T
Наличие на складе: Нет в наличии.
Описание:

The systematic description starts with basic theory and applications of different kinds of data structures, including storage structures and models. It also explores on data processing methods such as sorting, index and search technologies. Due to its numerous exercises the book is a helpful reference for graduate students, lecturers.


Opinion Analysis For Online Reviews

Автор: Lin Yuming Et Al
Название: Opinion Analysis For Online Reviews
ISBN: 9813100435 ISBN-13(EAN): 9789813100435
Издательство: World Scientific Publishing
Рейтинг:
Цена: 103490.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a comprehensive introduction on opinion analysis for online reviews. It offers the newest research on opinion mining, including theories, algorithms and datasets. A new feature presentation method is highlighted for sentiment classification. Then, a three-phase framework for sentiment classification is proposed, where a set of sentiment classifiers are selected automatically to make predictions. Such predictions are integrated via ensemble learning. Finally, to solve the problem of combination explosion encountered, a greedy algorithm is devised to select the base classifiers.

Data structures based on non-linear relations and data processing methods

Автор: Kai Fan, Xiang Ji, Xingni Zhou, Yanzhuo Ma, Zhiyuan Ren
Название: Data structures based on non-linear relations and data processing methods
ISBN: 3110676168 ISBN-13(EAN): 9783110676167
Издательство: Walter de Gruyter
Рейтинг:
Цена: 805810.00 T
Наличие на складе: Нет в наличии.
Описание:

The systematic description starts with basic theory and applications of different kinds of data structures, including storage structures and models. It also explores on data processing methods such as sorting, index and search technologies. Due to its numerous exercises the book is a helpful reference for graduate students, lecturers.


Data structures based on linear relations

Автор: Kai Fan, Xiang Ji, Xingni Zhou, Yanzhuo Ma, Zhiyuan Ren
Название: Data structures based on linear relations
ISBN: 3110593181 ISBN-13(EAN): 9783110593181
Издательство: Walter de Gruyter
Рейтинг:
Цена: 805810.00 T
Наличие на складе: Нет в наличии.
Описание:

Data structures is a key course for computer science and related majors. This book presents a variety of practical or engineering cases and derives abstract concepts from concrete problems. Besides basic concepts and analysis methods, it introduces basic data types such as sequential list, tree as well as graph. This book can be used as an undergraduate textbook, as a training textbook or a self-study textbook for engineers.


Quantum Machine Learning

Автор: Ashish Mani, Elizabeth Behrman, Indrajit Pan, Siddhartha Bhattacharyya, Sourav De, Susanta Chakraborti
Название: Quantum Machine Learning
ISBN: 3110670720 ISBN-13(EAN): 9783110670721
Издательство: Walter de Gruyter
Рейтинг:
Цена: 136310.00 T
Наличие на складе: Нет в наличии.
Описание:

Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system.

While many proposals of quantum machine learning algorithms are still purely theoretical and require a full-scale universal quantum computer to be tested, others have been implemented on small-scale or special purpose quantum devices.


Pattern Recognition and Machine Intelligence

Автор: Marzena Kryszkiewicz; Sanghamitra Bandyopadhyay; H
Название: Pattern Recognition and Machine Intelligence
ISBN: 3319199404 ISBN-13(EAN): 9783319199405
Издательство: Springer
Рейтинг:
Цена: 74530.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 6th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2015, held in Warsaw, Poland, in June/July 2015. The total of 53 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 90 submissions. They were organized in topical sections named: foundations of machine learning; image processing; image retrieval; image tracking; pattern recognition; data mining techniques for large scale data; fuzzy computing; rough sets; bioinformatics; and applications of artificial intelligence.


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