Handbook of Big Geospatial Data, Werner Martin, Chiang Yao-Yi
Автор: Aithal, Bharath H., Название: Building feature extraction with machine learning : ISBN: 1032255331 ISBN-13(EAN): 9781032255330 Издательство: Taylor&Francis Рейтинг: Цена: 12554.00 р. Наличие на складе: Поставка под заказ.
Описание: This book focuses on feature extraction methods for optical geospatial data using Machine Learning (ML). It is a practical guide for professionals and graduate students starting a career in information extraction. It explains spatial feature extraction in an easy-to-understand way and includes real case studies.
Автор: Roy Название: Handbook of Machine Learning Applications for Genomics ISBN: 9811691576 ISBN-13(EAN): 9789811691577 Издательство: Springer Рейтинг: Цена: 32142.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Currently, machine learning is playing a pivotal role in the progress of genomics. The applications of machine learning are helping all to understand the emerging trends and the future scope of genomics. This book provides comprehensive coverage of machine learning applications such as DNN, CNN, and RNN, for predicting the sequence of DNA and RNA binding proteins, expression of the gene, and splicing control. In addition, the book addresses the effect of multiomics data analysis of cancers using tensor decomposition, machine learning techniques for protein engineering, CNN applications on genomics, challenges of long noncoding RNAs in human disease diagnosis, and how machine learning can be used as a tool to shape the future of medicine. More importantly, it gives a comparative analysis and validates the outcomes of machine learning methods on genomic data to the functional laboratory tests or by formal clinical assessment. The topics of this book will cater interest to academicians, practitioners working in the field of functional genomics, and machine learning. Also, this book shall guide comprehensively the graduate, postgraduates, and Ph.D. scholars working in these fields.
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Автор: Werner Martin, Chiang Yao-Yi Название: Handbook of Big Geospatial Data ISBN: 3030554619 ISBN-13(EAN): 9783030554613 Издательство: Springer Цена: 32142.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A third perspective is taking a very practical perspective to big geospatial data, ranging from chapters that describe how big geospatial data infrastructures can be implemented and how specific applications can be implemented on top of big geospatial data.
Описание: Chapter 1. Concept of Digital Mapping.- Chapter 2. Different Approaches on Digital Mapping of Soil.- Chapter 3. Selection of Suitable Variables and Their Development.- Chapter 4. Digital Soil Mapping: Implementation and Assessment.- Chapter 5. Prediction Modelsfor Crop Mapping.- Chapter 6. Spatial Soil Moisture Prediction Model over an Agricultural Land.
Описание: Data Science, Big Data, and Artificial Intelligence are currently some of the most talked-about concepts in industry, government, and society, and yet also the most misunderstood. This book will clarify these concepts and provide you with practical knowledge to apply them. Featuring:- A comprehensive overview of the various fields of application of data science- Case studies from practice to make the described concepts tangible- Practical examples to help you carry out simple data analysis projectsThe book approaches the topic of data science from several sides. Crucially, it will show you how to build data platforms and apply data science tools and methods. Along the way, it will help you understand - and explain to various stakeholders - how to generate value from these techniques, such as applying data science to help organizations make faster decisions, reduce costs, and open up new markets. Furthermore, it will bring fundamental concepts related to data science to life, including statistics, mathematics, and legal considerations. Finally, the book outlines practical case studies that illustrate how knowledge generated from data is changing various industries over the long term. Contains these current issues:- Mathematics basics: Mathematics for Machine Learning to help you understand and utilize various ML algorithms.- Machine Learning: From statistical to neural and from Transformers and GPT-3 to AutoML, we introduce common frameworks for applying ML in practice- Natural Language Processing: Tools and techniques for gaining insights from text data and developing language technologies- Computer vision: How can we gain insights from images and videos with data science?- Modeling and Simulation: Model the behavior of complex systems, such as the spread of COVID-19, and do a What-If analysis covering different scenarios.- ML and AI in production: How to turn experimentation into a working data science product?- Presenting your results: Essential presentation techniques for data scientistsContributors: Stefan Papp / Wolfgang Weidinger / Katherine Munro / Bernhard Ortner / Annalisa Cadonna / Georg Langs / Roxane Licandro / Mario Meir-Huber / Danko Nikoli? / Zoltan Toth / Barbora Vesela / Rania Wazir / G?nther Zauner
Curious To Know More About Python Programming And Would Like To Go Proficient? Then Learn From The Best Tips and Tricks Laid Down In This Powerful Handbook
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Автор: Pradeep Kumar Garg Название: Digital Mapping of Soil Landscape Parameters ISBN: 9811532370 ISBN-13(EAN): 9789811532375 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Chapter 1. Concept of Digital Mapping.- Chapter 2. Different Approaches on Digital Mapping of Soil.- Chapter 3. Selection of Suitable Variables and Their Development.- Chapter 4. Digital Soil Mapping: Implementation and Assessment.- Chapter 5. Prediction Modelsfor Crop Mapping.- Chapter 6. Spatial Soil Moisture Prediction Model over an Agricultural Land.
Автор: Choo Kim-Kwang Raymond, Dehghantanha Ali Название: Handbook of Big Data Analytics and Forensics ISBN: 3030747522 ISBN-13(EAN): 9783030747527 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This handbook discusses challenges and limitations in existing solutions, and presents state-of-the-art advances from both academia and industry, in big data analytics and digital forensics. The second chapter comprehensively reviews IoT security, privacy, and forensics literature, focusing on IoT and unmanned aerial vehicles (UAVs). The authors propose a deep learning-based approach to process cloud’s log data and mitigate enumeration attacks in the third chapter. The fourth chapter proposes a robust fuzzy learning model to protect IT-based infrastructure against advanced persistent threat (APT) campaigns. Advanced and fair clustering approach for industrial data, which is capable of training with huge volume of data in a close to linear time is introduced in the fifth chapter, as well as offering an adaptive deep learning model to detect cyberattacks targeting cyber physical systems (CPS) covered in the sixth chapter. The authors evaluate the performance of unsupervised machine learning for detecting cyberattacks against industrial control systems (ICS) in chapter 7, and the next chapter presents a robust fuzzy Bayesian approach for ICS’s cyber threat hunting. This handbook also evaluates the performance of supervised machine learning methods in identifying cyberattacks against CPS. The performance of a scalable clustering algorithm for CPS’s cyber threat hunting and the usefulness of machine learning algorithms for MacOS malware detection are respectively evaluated. This handbook continues with evaluating the performance of various machine learning techniques to detect the Internet of Things malware. The authors demonstrate how MacOSX cyberattacks can be detected using state-of-the-art machine learning models. In order to identify credit card frauds, the fifteenth chapter introduces a hybrid model. In the sixteenth chapter, the editors propose a model that leverages natural language processing techniques for generating a mapping between APT-related reports and cyber kill chain. A deep learning-based approach to detect ransomware is introduced, as well as a proposed clustering approach to detect IoT malware in the last two chapters. This handbook primarily targets professionals and scientists working in Big Data, Digital Forensics, Machine Learning, Cyber Security Cyber Threat Analytics and Cyber Threat Hunting as a reference book. Advanced level-students and researchers studying and working in Computer systems, Computer networks and Artificial intelligence will also find this reference useful.
Автор: Maimon Название: Data Mining and Knowledge Discovery Handbook ISBN: 0387244352 ISBN-13(EAN): 9780387244358 Издательство: Springer Рейтинг: Цена: 30606.00 р. Наличие на складе: Поставка под заказ.
Описание: Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security.Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.
Автор: Sekimoto Название: Utilization of Geospatial Information in Daily Life ISBN: 9811969043 ISBN-13(EAN): 9789811969041 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on geospatial information in living spaces, providing many examples of its collection and use as well as discussing the problems of how it is used and its future prospects. Geospatial information science is in the process of evolving and being systematized, with the technical and usage aspects of the real world stimulating each other. This book systematizes the technical aspects of positioning; of geography, which manages and represents what is measured in units of earth coordinates; and of data science, which aims to efficiently express and process geographic information, all by introducing contemporary examples that are systematized with regard to their use in our living spaces. Examples of geospatial information used in almost all aspects of our lives, including urban areas, transportation, disaster prevention, health and medical care, agriculture, forestry and fisheries, culture, ecology, and topography, are presented, along with examples of their use in each area. One of the major features of this book is that it describes the use of data from earthquake disasters that is unique to Japan, as well as the use of open data and personal data in Japan, which is a trend that is gaining attention in many countries. In this way the book systematically describes events and circumstances in living spaces that are revealed by the expression and analysis of geospatial data, with case studies and discusses their use in the IoT era.
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