Machine Learning Techniques for Pattern Recognition and Information Security, Ankit Kumar Jain, Mohit Dua
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.
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: Leskovec Jure Название: Mining of Massive Datasets ISBN: 1108476341 ISBN-13(EAN): 9781108476348 Издательство: Cambridge Academ Рейтинг: Цена: 71810.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key problems in data mining, with exercises suitable for students from the advanced undergraduate level and beyond. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.
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: Ankit Kumar Jain, Mohit Dua Название: Machine Learning Techniques for Pattern Recognition and Information Security ISBN: 1799833003 ISBN-13(EAN): 9781799833000 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 179250.00 T Наличие на складе: Нет в наличии. Описание: The artificial intelligence subset machine learning has become a popular technique in professional fields as many are finding new ways to apply this trending technology into their everyday practices. Two fields that have majorly benefited from this are pattern recognition and information security. The ability of these intelligent algorithms to learn complex patterns from data and attain new performance techniques has created a wide variety of uses and applications within the data security industry. There is a need for research on the specific uses machine learning methods have within these fields, along with future perspectives.
Machine Learning Techniques for Pattern Recognition and Information Security is a collection of innovative research on the current impact of machine learning methods within data security as well as its various applications and newfound challenges. While highlighting topics including anomaly detection systems, biometrics, and intrusion management, this book is ideally designed for industrial experts, researchers, IT professionals, network developers, policymakers, computer scientists, educators, and students seeking current research on implementing machine learning tactics to enhance the performance of information security.
Автор: Witten, Ian H. Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed. ISBN: 0128042915 ISBN-13(EAN): 9780128042915 Издательство: Elsevier Science Рейтинг: Цена: 61750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: Munish Kumar, Manish Kumar Jindal, Simpel Rani Jindal, R. K. Sharma, Anupam Garg Название: Feature Extraction and Classification Techniques for Text Recognition ISBN: 1799824063 ISBN-13(EAN): 9781799824060 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 257790.00 T Наличие на складе: Нет в наличии. Описание: Presents innovative research on the fusion and hybridization of various features and classifiers for document analysis and recognition. The book highlights a range of topics, including adaptive boosting, writer identification, and signature verification.
Название: Scaling up machine learning ISBN: 1108461743 ISBN-13(EAN): 9781108461740 Издательство: Cambridge Academ Рейтинг: Цена: 49630.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: Watt, Jeremy (northwestern University, Illinois) Borhani, Reza (northwestern University, Illinois) Katsaggelos, Aggelos (northwestern University, Illi Название: Machine learning refined ISBN: 1108480721 ISBN-13(EAN): 9781108480727 Издательство: Cambridge Academ Рейтинг: Цена: 84480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: An intuitive approach to machine learning detailing the key concepts needed to build products and conduct research. Featuring color illustrations, real-world examples, practical coding exercises, and an online package including sample code, data sets, lecture slides, and solutions. It is ideal for graduate courses, reference, and self-study.
Автор: Ramgopal Kashyap, A.V. Senthil Kumar Название: Challenges and Applications for Implementing Machine Learning in Computer Vision ISBN: 1799801829 ISBN-13(EAN): 9781799801825 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 174630.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presents research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. The book highlights a wide range of topics such as video segmentation, object recognition, and 3D modelling.
Автор: Munish Kumar, Manish Kumar Jindal, Simpel Rani Jindal, R. K. Sharma, Anupam Garg Название: Feature Extraction and Classification Techniques for Text Recognition ISBN: 1799824071 ISBN-13(EAN): 9781799824077 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 194970.00 T Наличие на складе: Невозможна поставка. Описание: Presents research on the fusion and hybridization of various features and classifiers for document analysis and recognition. The book provides coverage of a range of topics, including adaptive boosting, writer identification, and signature verification.
Автор: Jose Garcia-Rodriguez Название: Advancements in Computer Vision and Image Processing ISBN: 1522556281 ISBN-13(EAN): 9781522556282 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 180180.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Interest in computer vision and image processing has grown in recent years with the advancement of everyday technologies such as smartphones, computer games, and social robotics. These advancements have allowed for advanced algorithms that have improved the processing capabilities of these technologies.Advancements in Computer Vision and Image Processing is a critical scholarly resource that explores the impact of new technologies on computer vision and image processing methods in everyday life. Featuring coverage on a wide range of topics including 3D visual localization, cellular automata-based structures, and eye and face recognition, this book is geared toward academicians, technology professionals, engineers, students, and researchers seeking current research on the development of sophisticated algorithms to process images and videos in real time.
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