Artificial Intelligence In Data Mining
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Artificial Intelligence In Data Mining
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Author : D. Binu
language : en
Publisher: Academic Press
Release Date : 2021-02-17
Artificial Intelligence In Data Mining written by D. Binu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-17 with Science categories.
Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area. - Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering - Presents coverage of key topics such as heuristic methods for data clustering, deep learning methods for data classification, and neural networks - Includes case studies and real-world applications of AI techniques in data mining, for improved outcomes in clinical diagnosis, satellite data extraction, agriculture, security and defense
Artificial Intelligence And Data Mining In Healthcare
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Author : Malek Masmoudi
language : en
Publisher: Springer Nature
Release Date : 2021-01-25
Artificial Intelligence And Data Mining In Healthcare written by Malek Masmoudi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-25 with Computers categories.
This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection. The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.
Artificial Intelligence And Machine Learning For Business
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Author : Oliver Tensor
language : en
Publisher: Smart Creative Publishing
Release Date : 2020-10-13
Artificial Intelligence And Machine Learning For Business written by Oliver Tensor and has been published by Smart Creative Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-13 with categories.
Are you a new business owner? Or an entrepreneur looking to catch up to the big companies in your industrial sector? If you want to understand and master the fundamentals and importance of data science technologies to kick start your business or take it to the next level, then keep reading. Thanks to the smart and savvy customer of today, the competition to gain new customers while retaining the existing customers is fierce. As a result, companies are increasingly relying upon cutting edge technologies such as big data analytics, data mining technology, machine learning, and artificial intelligence technology to gain an edge over the competition.Today, machine learning and artificial intelligence have given rise to sophisticated machines that can study human behavior and activity to identify underlying human behavioral patterns and precisely predict what products and services consumers are interested in. Businesses with an eye on the future are gradually turning into technology companies under the façade of their intended business model. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. Those entrepreneurs and business executives who have a sound understanding of the current challenges and status of their business will be primed to make informed decisions to meet the challenges head-on and improve their bottom line. Receive overarching guidance on how you can adopt any and all of the Data Science technologies in your business model to accelerate your growth rate. Learn how researchers are breaking the boundaries of data science to mimic human intelligence in machines. Learn the data science lifecycle in such extensive detail that you will be fully prepared to initiate and complete a data science implementation project in your business. Learn all about the historical development to the current explosion in this field of Big Data Analytics and how it differs data visualization techniques. Dig deep into the data mining process, the benefits of using data mining technology, the challenges facing the data mining technology and learn about some data mining tools that you can leverage for your business. Gain an in-depth understanding of various machine learning algorithms do assess the best Machine learning algorithm applicable to your business model. Learn the very important concept of data science and machine learning Decision Trees, applicable to small and large businesses across the industrial spectrum, explained thoroughly using real-life examples for ease of understanding. Master the concept of sales and marketing funnel along with the tools available for sales funnel analytics in the market today. Deep dive into the concept of personalized marketing, predictive analytics, customer analytics, and exploratory data analysis presented with details on how you can make sense out of all your customer behavioral data. This book is filled with real-life examples to help you understand the nitty-gritty of all the concepts as well as names and description of multiple tools that you can further explore and selectively implement in your business to reap the benefits of these cutting-edge technologies. Would You Like to Know More? Get This Book Today to get access to Artificial Intelligence and Machine Learning power.
Computational Intelligence In Data Mining
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Author : Giacomo Della Riccia
language : en
Publisher: Springer
Release Date : 2014-05-04
Computational Intelligence In Data Mining written by Giacomo Della Riccia and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-04 with Computers categories.
The book aims to merge Computational Intelligence with Data Mining, which are both hot topics of current research and industrial development, Computational Intelligence, incorporates techniques like data fusion, uncertain reasoning, heuristic search, learning, and soft computing. Data Mining focuses on unscrambling unknown patterns or structures in very large data sets. Under the headline "Discovering Structures in Large Databases” the book starts with a unified view on ‘Data Mining and Statistics – A System Point of View’. Two special techniques follow: ‘Subgroup Mining’, and ‘Data Mining with Possibilistic Graphical Models’. "Data Fusion and Possibilistic or Fuzzy Data Analysis” is the next area of interest. An overview of possibilistic logic, nonmonotonic reasoning and data fusion is given, the coherence problem between data and non-linear fuzzy models is tackled, and outlier detection based on learning of fuzzy models is studied. In the domain of "Classification and Decomposition” adaptive clustering and visualisation of high dimensional data sets is introduced. Finally, in the section "Learning and Data Fusion” learning of special multi-agents of virtual soccer is considered. The last topic is on data fusion based on stochastic models.
Data Science
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Author : Richard Hurley
language : en
Publisher:
Release Date : 2019-11-02
Data Science written by Richard Hurley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-02 with Big data categories.
If you want to learn about data science and big data, then keep reading... Two manuscripts in one book: Data Science: What You Need to Know About Data Analytics, Data Mining, Regression Analysis, Artificial Intelligence, Big Data for Business, Data Visualization, Database Querying, and Machine Learning Big Data: A Guide to Big Data Trends, Artificial Intelligence, Machine Learning, Predictive Analytics, Internet of Things, Data Science, Data Analytics, Business Intelligence, and Data Mining This book will discuss everything that you need to know when it comes to working in the field of data science. This world has changed, and with the modern technology that we have, it is easier than ever for companies to amass a large amount of data on the industry, on their competition, on their products, and their customers. Gathering the data is the easy part, though. Being able to sort through this data and understand what it is saying is going to be a unique challenge all on its own. This is where the process and field of data science can come in. There is so much that we can explore and learn about when it comes to the world of data science, and this ultimate guide is here to help you navigate through these specialties. You will see just how important the ideas of data mining, data analytics, and even artificial intelligence are to our world as a whole today. Some of the topics covered in part 1 of this book include: What is Data Science? What Exactly Does a Data Scientist Do? A Look at What Data Analytics Is All About What is Data Mining and How Does It Fit in with Data Science? Regression Analysis Why is Data Visualization So Important When It Comes to Understanding Your Data? How to work with Database Querying A Look at Artificial Intelligence What is Machine Learning and How Is It Different from Artificial Intelligence? What is the Future of Artificial Intelligence and Machine Learning? And much more! Some of the topics covered in part 2 of this book include: What is big data, and why is it important? The five V's behind big data How big data is already impacting your life, and where big data may be headed How big data and your everyday devices and appliances will come together in unexpected ways via the Internet of Things How companies and governments are using predictive analytics to get ahead of the competition or improve service How big data is used for fraud detection How big data can train intelligent computer systems The many ways large corporations are benefiting from big data and the tools that use it like machine learning, AI, and predictive analytics Upcoming trends in big data that are sure to have a large impact on your future Artificial intelligence, and how big data drives its development What machine learning is and how it is tied to big data The relationship between big data, data analytics, and business intelligence Insights into how big data impacts privacy issues The pros and cons regarding big data And much, much more! So if you want to learn more about data science and big data, click the "add to cart" button!
Artificial Intelligence And Data Mining Approaches In Security Frameworks
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Author : Neeraj Bhargava
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-24
Artificial Intelligence And Data Mining Approaches In Security Frameworks written by Neeraj Bhargava and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-24 with Technology & Engineering categories.
ARTIFICIAL INTELLIGENCE AND DATA MINING IN SECURITY FRAMEWORKS Written and edited by a team of experts in the field, this outstanding new volume offers solutions to the problems of security, outlining the concepts behind allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Artificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to artificial intelligence. Successful application of security frameworks to enable meaningful, cost effective, personalized security service is a primary aim of engineers and researchers today. However realizing this goal requires effective understanding, application and amalgamation of AI and data mining and several other computing technologies to deploy such a system in an effective manner. This book provides state of the art approaches of artificial intelligence and data mining in these areas. It includes areas of detection, prediction, as well as future framework identification, development, building service systems and analytical aspects. In all these topics, applications of AI and data mining, such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms, are explained and explored. This book is aimed at the modeling and performance prediction of efficient security framework systems, bringing to light a new dimension in the theory and practice. This groundbreaking new volume presents these topics and trends, bridging the research gap on AI and data mining to enable wide-scale implementation. Whether for the veteran engineer or the student, this is a must-have for any library. This groundbreaking new volume: Clarifies the understanding of certain key mechanisms of technology helpful in the use of artificial intelligence and data mining in security frameworks Covers practical approaches to the problems engineers face in working in this field, focusing on the applications used every day Contains numerous examples, offering critical solutions to engineers and scientists Presents these new applications of AI and data mining that are of prime importance to human civilization as a whole
Integration Challenges For Analytics Business Intelligence And Data Mining
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Author : Azevedo, Ana
language : en
Publisher: IGI Global
Release Date : 2020-12-11
Integration Challenges For Analytics Business Intelligence And Data Mining written by Azevedo, Ana and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-11 with Computers categories.
As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration. Integration Challenges for Analytics, Business Intelligence, and Data Mining is a relevant academic book that provides empirical research findings on increasing the understanding of using data mining in the context of business intelligence and analytics systems. Covering topics that include big data, artificial intelligence, and decision making, this book is an ideal reference source for professionals working in the areas of data mining, business intelligence, and analytics; data scientists; IT specialists; managers; researchers; academicians; practitioners; and graduate students.
Data Mining
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Author : Graham J. Williams
language : en
Publisher: Springer
Release Date : 2006-01-22
Data Mining written by Graham J. Williams and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-22 with Computers categories.
This volume provides a snapshot of the current state of the art in data mining, presenting it both in terms of technical developments and industrial applications. The collection of chapters is based on works presented at the Australasian Data Mining conferences and industrial forums. Authors include some of Australia's leading researchers and practitioners in data mining. The volume also contains chapters by regional and international authors.
Data Mining And Machine Learning Applications
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Author : Rohit Raja
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-26
Data Mining And Machine Learning Applications written by Rohit Raja and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-26 with Computers categories.
DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.
Data Mining
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Author : Ian H. Witten
language : en
Publisher: Morgan Kaufmann
Release Date : 2000
Data Mining written by Ian H. Witten and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.
This book offers a thorough grounding in machine learning concepts combined with practical advice on applying machine learning tools and techniques in real-world data mining situations. Clearly written and effectively illustrated, this book is ideal for anyone involved at any level in the work of extracting usable knowledge from large collections of data. Complementing the book's instruction is fully functional machine learning software.