Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques


Book Description

"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.




Handbook of Research on Artificial Intelligence in Government Practices and Processes


Book Description

In today’s global culture where the internet has established itself as a main tool of communication, the global system of economy and regulations, as well as data and decisions based on data analysis, have become essential for public actors and institutions. Governments need to be updated and use the latest technologies to understand what society’s demands are, and user behavioral data, which can be pulled by intelligent applications, can offer tremendous insights into this. The Handbook of Research on Artificial Intelligence in Government Practices and Processes identifies definitional perspectives of behavioral data science and what its use by governments means for automation, predictability, and risks to privacy and free decision making in society. Many governments can train their algorithms to work with machine learning, leading to the capacity to interfere in the behavior of society and potentially achieve a change in societal behavior without society itself even being aware of it. As such, the use of artificial intelligence by governments has raised concerns about privacy and personal security issues. Covering topics such as digital democracy, data extraction techniques, and political communications, this book is an essential resource for data analysts, politicians, journalists, public figures, executives, researchers, data specialists, communication specialists, digital marketers, and academicians.




Handbook of Statistical Analysis and Data Mining Applications


Book Description

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications




Handbook of Research on Emerging Trends and Applications of Machine Learning


Book Description

As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.




Data Clustering: Theory, Algorithms, and Applications, Second Edition


Book Description

Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.




Philosophy of Artificial Intelligence and Its Place in Society


Book Description

The early 2020s have been marked by a surge of interest in artificial intelligence (AI), and it has grown to be one of the hottest topics in computer science, business technology research, and educational technologies. Despite AI winters in the 1970s and 1990s, where interest and subsequently adequate funding for AI research ceased, and as the technology and its usefulness become more perceptible, often with brilliant results, society is once again ready to investigate this powerful technology and its potential. However, a challenge arises when AI is called into question in an ethical context. It is important that we explore how it can contribute to the resolution of ethical, social, and environmental issues and also to address growing concerns around AI developing emergent bias as well as the human application of AI for malicious purposes. With recent AI-based writing technologies, concerns around academic integrity abound and challenge our perceptions of authenticity in writing. A careful assessment of these technologies, their usefulness and potential harm, and strategic solutions to maintaining ethical standards and regulation of the technology is a necessity for the maintenance of civilized life amidst these tools. Philosophy of Artificial Intelligence and Its Place in Society evaluates various aspects of artificial intelligence including the range of technologies, their advantages and disadvantages, and how AI systems operate. Spanning from machine learning to deep learning, philosophical insights, societal concerns, and the newest approaches to AI, it helps to develop an appreciation for and breadth of knowledge across the full range of AI sub-disciplines including neural networks, evolutionary computation, computer vision, robotics, expert systems, speech processing, and natural language processing. Led Dr. Luiz Moutinho of the University of Suffolk in the United Kingdom, who has won several awards for his academic literature, this book provides academic market-scholars; researchers and students of philosophy, sociology, economics, and education; as well as corporate scientists with a comprehensive collection of core research elements, concepts, advances, applications, evidence, and outcomes related to artificial intelligence.




Advances in Machine Learning and Computational Intelligence


Book Description

This book gathers selected high-quality papers presented at the International Conference on Machine Learning and Computational Intelligence (ICMLCI-2019), jointly organized by Kunming University of Science and Technology and the Interscience Research Network, Bhubaneswar, India, from April 6 to 7, 2019. Addressing virtually all aspects of intelligent systems, soft computing and machine learning, the topics covered include: prediction; data mining; information retrieval; game playing; robotics; learning methods; pattern visualization; automated knowledge acquisition; fuzzy, stochastic and probabilistic computing; neural computing; big data; social networks and applications of soft computing in various areas.




The Text Mining Handbook


Book Description

Publisher description




Handbook of Statistical Analysis and Data Mining Applications


Book Description

The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions. - Written "By Practitioners for Practitioners" - Non-technical explanations build understanding without jargon and equations - Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models - Practical advice from successful real-world implementations - Includes extensive case studies, examples, MS PowerPoint slides and datasets - CD-DVD with valuable fully-working 90-day software included: "Complete Data Miner - QC-Miner - Text Miner" bound with book




Cognitive Analytics: Concepts, Methodologies, Tools, and Applications


Book Description

Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians.