Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics: Theories and Applications, Chiroma Haruna, Abdulhamid Shafi`i M., Fournier-Viger Philippe
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: MALLICK & BORAH Название: Emerging Trends and Applications in Cognitive Computing ISBN: 1522557938 ISBN-13(EAN): 9781522557937 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 179740.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Though an individual can process a limitless amount of information, the human brain can only comprehend a small amount of data at a time. Using technology can improve the process and comprehension of information, but the technology must learn to behave more like a human brain to employ concepts like memory, learning, visualization ability, and decision making.Emerging Trends and Applications in Cognitive Computing is a fundamental scholarly source that provides empirical studies and theoretical analysis to show how learning methods can solve important application problems throughout various industries and explain how machine learning research is conducted. Including innovative research on topics such as deep neural networks, cyber-physical systems, and pattern recognition, this collection of research will benefit individuals such as IT professionals, academicians, students, researchers, and managers.
Автор: Versace Christopher J., Hawkins Lenore Elle Название: Power Trend Investing: Transforming Everyday Noise Into Investable Signals and Profiting from Emerging Trends in Today`s Economy ISBN: 1119003946 ISBN-13(EAN): 9781119003946 Издательство: Wiley Рейтинг: Цена: 24280.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The automatic filter against bad, irrelevant, outdated investing information Cocktail Investing takes a look at investing in a different, catalyst-driven light to form a more cohesive, globally relevant investing lens.
Автор: Rik Das, Siddhartha Bhattacharyya, Sudarshan Nandy Название: Machine Learning Applications: Emerging Trends ISBN: 3110608669 ISBN-13(EAN): 9783110608663 Издательство: Walter de Gruyter Рейтинг: Цена: 123910.00 T Наличие на складе: Нет в наличии. Описание:
The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.
Автор: Rik Das, Siddhartha Bhattacharyya, Sudarshan Nandy Название: Machine Learning Applications: Emerging Trends ISBN: 3110608537 ISBN-13(EAN): 9783110608533 Издательство: Walter de Gruyter Цена: 123910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.
Автор: Omowunmi E. Isafiade, Antoine B. Bagula, Название: Data Mining Trends and Applications in Criminal Science and Investigations ISBN: 152250463X ISBN-13(EAN): 9781522504634 Издательство: Turpin Рейтинг: Цена: 206970.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The field of data mining is receiving significant attention in today's information-rich society, where data is available from different sources and formats, in large volumes, and no longer constitutes a bottleneck for knowledge acquisition. This rich information has paved the way for novel areas of research, particularly in the crime data analysis realm.Data Mining Trends and Applications in Criminal Science and Investigations presents scientific concepts and frameworks of data mining and analytics implementation and uses across various domains, such as public safety, criminal investigations, intrusion detection, crime scene analysis, and suspect modeling. Exploring the diverse ways that data is revolutionizing the field of criminal science, this publication meets the research needs of law enforcement professionals, data analysts, investigators, researchers, and graduate-level students.
Название: Handbook of research on emerging trends and applications of machine learning ISBN: 1522596437 ISBN-13(EAN): 9781522596431 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 335410.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, the book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science.
Автор: Cao Название: Trends and Applications in Knowledge Discovery and Data Mining ISBN: 3319429957 ISBN-13(EAN): 9783319429953 Издательство: Springer Рейтинг: Цена: 46590.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the thoroughly refereed post-workshop proceedings at PAKDD Workshops 2016, held in conjunction with PAKDD, the 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining in Auckland, New Zealand, in April 2016. The 23 revised papers presented were carefully reviewed and selected from 38 submissions.
Автор: Mendlowitz Cpa Edward Название: How to Read, Analyze and Use Financial Statements Including Ratio and Trend Analysis: Financial Accounting: End-User Applications ISBN: 1716893399 ISBN-13(EAN): 9781716893391 Издательство: Неизвестно Рейтинг: Цена: 28370.00 T Наличие на складе: Нет в наличии. Описание: This book is focused on the information needs of the users of financial statements that include, but is not limited to, managers, investors, creditors, and regulators. The primary context of the course is financial accounting for corporate entities. This course assumes no prior knowledge of financial accounting. From my course syllabus: Upon successful completion of this course students will be able to: 1. Understand what comprises a complete financial statement 2. Comfortably review a financial statement 3. Be able to perform a basic analysis of a financial statement 4. Gain familiarity with accounting terminology and concepts 5. Become familiar with Generally Accepted Accounting Principles (GAAP). 6. Understand the roles of each of the seven elements of a financial statement 7. Gain an understanding of internal controls 8. Be introduced to the role of ethics in accounting
Автор: Leong Hou U.; Hady W. Lauw Название: Trends and Applications in Knowledge Discovery and Data Mining ISBN: 3030261417 ISBN-13(EAN): 9783030261412 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 14th Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2019).- A Supporting Tool for IT System Security Specification Evaluation Based on ISO/IEC 15408 and ISO/IEC 18045.- An Investigation on Multi View based User Behavior towards Spam Detection in Social Networks.- A Cluster Ensemble Strategy for Asian Handicap Betting.- Designing an Integrated Intelligence Center: New Taipei City Police Department as an Example.- Early Churn User Classification in Social Networking Service Using Attention-based Long Short-Term Memory.- PAKDD 2019 Workshop on Weakly Supervised Learning: Progress and Future (WeL 2019).- Weakly Supervised Learning by a Confusion Matrix of Contexts.- Learning a Semantic Space for Modeling Images, Tags and Feelings in Cross-media Search.- Adversarial Active Learning in the Presence of Weak and Malicious Oracles.- The Most Related Knowledge First: A Progressive Domain Adaptation Method.- Learning Data Representation for Clustering (LDRC 2019).- Deep Architectures for Joint Clustering and Visualization with Self-Organizing Maps.- Deep cascade of extra trees.- Algorithms for an Efficient Tensor Biclustering.- Change point detetion in periodic panel data using a mixture-model-based approach.- The 8th Workshop on Biologically-inspired Techniques for Knowledge Discovery and Data Mining (BDM 2019).- Neural Network-Based Deep Encoding for Mixed-Attribute Data Classification.- Protein Complexes Detection Based on Deep Neural Network.- Predicting Auction Price of Vehicle License Plate with Deep Residual Learning.- Mining Multispectral Aerial Images for Automatic Detection of Strategic Bridge Locations for Disaster Relief Missions.- Chinese Word Segmentation with Feature Alignment.- Spike Sorting with Locally Weighted Co-association Matrix-based Spectral Clustering.- Label Distribution Learning Based Age-Invariant Face Recognition.- Overall Loss For Deep Neural Networks.- Sentiment Analysis Based on LSTM Architecture with Emoticon Attention.- Aspect Level Sentiment Analysis with Aspect Attention.- The 1st Pacific Asia Workshop on Deep Learning for Knowledge Transfer (DLKT 2019).- Transfer Channel Pruning for Compressing Deep Domain Adaptation Models.- A Heterogeneous Domain Adversarial Neural Network for Trans-Domain Behavioral Targeting.- Natural Language Business Intelligence Question Answering through SeqtoSeq Transfer Learning.- Robust Faster R-CNN: Increasing Robustness to Occlusions and multi-scale objects.- Effectively Representing Short Text via the Improved Semantic Feature Space Mapping.- Probabilistic Graphical Model Based Highly Scalable Directed Community Detection Algorithm.- Hilltop based recommendation in co-author networks.- Neural Variational Collaborative Filtering for Top-K Recommendation.
This book constitutes the refereed proceedings of five workshops that were held in conjunction with the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2021, in Delhi, India, in May 2021.
The 17 revised full papers presented were carefully reviewed and selected from a total of 39 submissions..
The five workshops were as follows:
Workshop on Smart and Precise Agriculture (WSPA 2021)
PAKDD 2021 Workshop on Machine Learning for Measurement Informatics (MLMEIN 2021)
The First Workshop and Shared Task on Scope Detection of the Peer Review Articles (SDPRA 2021)
The First International Workshop on Data Assessment and Readiness for AI (DARAI 2021)
The First International Workshop on Artificial Intelligence for Enterprise Process Transformation (AI4EPT 2021)
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