Artificial Intelligence In Data Mining

Machine Learning And Data Mining In Aerospace Technology Book PDF
✏Book Title : Machine Learning and Data Mining in Aerospace Technology
✏Author : Aboul Ella Hassanien
✏Publisher : Springer
✏Release Date : 2019-07-02
✏Pages : 232
✏ISBN : 9783030202125
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Machine Learning and Data Mining in Aerospace Technology Book Summary : This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites are the ‘eagle eyes’ that allow us to view massive areas of the Earth simultaneously, and can gather more data, more quickly, than tools on the ground. Consequently, the development of intelligent health monitoring systems for artificial satellites – which can determine satellites’ current status and predict their failure based on telemetry data – is one of the most important current issues in aerospace engineering. This book is divided into three parts, the first of which discusses central problems in the health monitoring of artificial satellites, including tensor-based anomaly detection for satellite telemetry data and machine learning in satellite monitoring, as well as the design, implementation, and validation of satellite simulators. The second part addresses telemetry data analytics and mining problems, while the last part focuses on security issues in telemetry data.

Artificial Intelligence And Data Mining In Healthcare Book PDF
✏Book Title : Artificial Intelligence and Data Mining in Healthcare
✏Author : Malek Masmoudi
✏Publisher : Springer
✏Release Date : 2020-09-11
✏Pages : 182
✏ISBN : 3030452395
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Artificial Intelligence and Data Mining in Healthcare Book Summary : 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.

Data Mining Practical Machine Learning Tools And Techniques Book PDF
✏Book Title : Data Mining Practical Machine Learning Tools and Techniques
✏Author : Ian H. Witten
✏Publisher : Elsevier
✏Release Date : 2011-02-03
✏Pages : 664
✏ISBN : 9780080890364
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Data Mining Practical Machine Learning Tools and Techniques Book Summary : Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization

Machine Learning And Data Mining In Materials Science Book PDF
✏Book Title : Machine Learning and Data Mining in Materials Science
✏Author : Norbert Huber
✏Publisher : Frontiers Media SA
✏Release Date : 2020-04-22
✏Pages :
✏ISBN : 9782889636518
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Machine Learning and Data Mining in Materials Science Book Summary :

Artificial Intelligence And Data Mining For Mergers And Acquisitions Book PDF
✏Book Title : Artificial Intelligence and Data Mining for Mergers and Acquisitions
✏Author : Debasis Chanda
✏Publisher : CRC Press
✏Release Date : 2021-03-18
✏Pages : 304
✏ISBN : 1138354732
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Artificial Intelligence and Data Mining for Mergers and Acquisitions Book Summary : The goal of this work is to present a modeling framework for Virtual Enterprise focused on process composition by consolidating individual process models into consolidated process model. This framework uses Artificial Intelligence Knowledge Bases and also proposes a Data Mining model using a fuzzy mathematical approach.

Advances In Machine Learning And Data Mining For Astronomy Book PDF
✏Book Title : Advances in Machine Learning and Data Mining for Astronomy
✏Author : Michael J. Way
✏Publisher : CRC Press
✏Release Date : 2012-03-29
✏Pages : 744
✏ISBN : 9781439841730
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Advances in Machine Learning and Data Mining for Astronomy Book Summary : Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book’s introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.

📒Data Mining ✍ Ian H. Witten

Data Mining Book PDF
✏Book Title : Data Mining
✏Author : Ian H. Witten
✏Publisher : Morgan Kaufmann
✏Release Date : 2016-10-01
✏Pages : 654
✏ISBN : 9780128043578
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Data Mining Book Summary : 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 http://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

Mathematical Analysis For Machine Learning And Data Mining Book PDF
✏Book Title : Mathematical Analysis for Machine Learning and Data Mining
✏Author : Simovici Dan A
✏Publisher : World Scientific
✏Release Date : 2018-05-21
✏Pages : 984
✏ISBN : 9789813229709
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Mathematical Analysis for Machine Learning and Data Mining Book Summary : This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The mathematical analysis component of the typical mathematical curriculum for computer science students omits these very important ideas and techniques which are indispensable for approaching specialized area of machine learning centered around optimization such as support vector machines, neural networks, various types of regression, feature selection, and clustering. The book is of special interest to researchers and graduate students who will benefit from these application areas discussed in the book.

Machine Learning And Data Mining For Computer Security Book PDF
✏Book Title : Machine Learning and Data Mining for Computer Security
✏Author : Marcus A. Maloof
✏Publisher : Springer Science & Business Media
✏Release Date : 2006-02-28
✏Pages : 210
✏ISBN : 9781846282539
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Machine Learning and Data Mining for Computer Security Book Summary : "Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This book has a strong focus on information processing and combines and extends results from computer security. The first part of the book surveys the data sources, the learning and mining methods, evaluation methodologies, and past work relevant for computer security. The second part of the book consists of articles written by the top researchers working in this area. These articles deals with topics of host-based intrusion detection through the analysis of audit trails, of command sequences and of system calls as well as network intrusion detection through the analysis of TCP packets and the detection of malicious executables. This book fills the great need for a book that collects and frames work on developing and applying methods from machine learning and data mining to problems in computer security.

Machine Learning And Data Mining In Pattern Recognition Book PDF
✏Book Title : Machine Learning and Data Mining in Pattern Recognition
✏Author : Petra Perner
✏Publisher : Springer
✏Release Date : 2018-08-19
✏Pages : 485
✏ISBN : 9783319961330
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Machine Learning and Data Mining in Pattern Recognition Book Summary : This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

Machine Learning And Data Mining In Pattern Recognition Book PDF
✏Book Title : Machine Learning and Data Mining in Pattern Recognition
✏Author :
✏Publisher :
✏Release Date : 2001
✏Pages :
✏ISBN : UOM:39015049127809
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Machine Learning and Data Mining in Pattern Recognition Book Summary :

Textbook Of Machine Learning And Data Mining Book PDF
✏Book Title : Textbook of Machine Learning and Data Mining
✏Author : Hiroshi Mamitsuka
✏Publisher :
✏Release Date : 2018-09-12
✏Pages : 388
✏ISBN : 4991044502
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Textbook of Machine Learning and Data Mining Book Summary : Data-driven approaches, particularly machine learning and data mining, are the main driving force of the current artificial intelligence technology. This book covers a wide variety of methods in machine learning and data mining, dividing them from a viewpoint of data types, which begin with rather simple vectors and end by graphs and also combination of different data types. This book describes standard techniques of machine learning and data mining for each data type, especially focusing on the relevance and difference among them. Also after explaining a series of machine learning methods for seven different data types, this book has a chapter for standard validation methods on empirical results obtained by applying machine learning methods to data. This book can be used for a variety of objectives, including an introductory textbook of studying machine learning and a (first step) book to start machine learning research, etc.

Machine Learning And Data Mining Book PDF
✏Book Title : Machine Learning and Data Mining
✏Author : Igor Kononenko
✏Publisher : Elsevier
✏Release Date : 2007-04-30
✏Pages : 480
✏ISBN : 9780857099440
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Machine Learning and Data Mining Book Summary : Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining. Suitable for advanced undergraduates and their tutors at postgraduate level in a wide area of computer science and technology topics as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to the libraries and bookshelves of the many companies who are using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions. Provides an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining A valuable addition to the libraries and bookshelves of companies using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions

Introduction To Algorithms For Data Mining And Machine Learning Book PDF
✏Book Title : Introduction to Algorithms for Data Mining and Machine Learning
✏Author : Xin-She Yang
✏Publisher : Academic Press
✏Release Date : 2019-07-15
✏Pages : 188
✏ISBN : 9780128172162
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Introduction to Algorithms for Data Mining and Machine Learning Book Summary : Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data. Presents an informal, theorem-free approach with concise, compact coverage of all fundamental topics Includes worked examples that help users increase confidence in their understanding of key algorithms, thus encouraging self-study Provides algorithms and techniques that can be implemented in any programming language, with each chapter including notes about relevant software packages

Encyclopedia Of Machine Learning And Data Mining Book PDF
✏Book Title : Encyclopedia of Machine Learning and Data Mining
✏Author : Claude Sammut
✏Publisher :
✏Release Date :
✏Pages :
✏ISBN : 1489975020
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Encyclopedia of Machine Learning and Data Mining Book Summary :

📒Machine Learning And Data Mining ✍ Ryszad S. Michalski

Machine Learning And Data Mining Book PDF
✏Book Title : Machine Learning and Data Mining
✏Author : Ryszad S. Michalski
✏Publisher : Wiley
✏Release Date : 1998-04-22
✏Pages : 472
✏ISBN : 0471971995
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Machine Learning and Data Mining Book Summary : Master the new computational tools to get the most out of your information system. This practical guide, the first to clearly outline the situation for the benefit of engineers and scientists, provides a straightforward introduction to basic machine learning and data mining methods, covering the analysis of numerical, text, and sound data.

Machine Learning And Data Mining For Sports Analytics Book PDF
✏Book Title : Machine Learning and Data Mining for Sports Analytics
✏Author : Ulf Brefeld
✏Publisher : Springer
✏Release Date : 2019-04-06
✏Pages : 179
✏ISBN : 9783030172749
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Machine Learning and Data Mining for Sports Analytics Book Summary : This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018. The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individual sports cycling and martial arts. In addition, four challenge papers are included, reporting on how to predict pass receivers in soccer.

Nature Inspired Computation In Data Mining And Machine Learning Book PDF
✏Book Title : Nature Inspired Computation in Data Mining and Machine Learning
✏Author : Xin-She Yang
✏Publisher : Springer Nature
✏Release Date : 2019-09-03
✏Pages : 273
✏ISBN : 9783030285531
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Nature Inspired Computation in Data Mining and Machine Learning Book Summary : This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.

Machine Learning Techniques In Data Mining Applications Book PDF
✏Book Title : MACHINE LEARNING TECHNIQUES IN DATA MINING APPLICATIONS
✏Author : DR. SUBHENDU KUMAR PANI
✏Publisher : Lulu.com
✏Release Date :
✏Pages :
✏ISBN : 9781365016240
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏MACHINE LEARNING TECHNIQUES IN DATA MINING APPLICATIONS Book Summary :

Data Mining And Machine Learning Book PDF
✏Book Title : Data Mining and Machine Learning
✏Author : Mohammed J. Zaki
✏Publisher : Cambridge University Press
✏Release Date : 2020-01-31
✏Pages : 775
✏ISBN : 9781108473989
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Data Mining and Machine Learning Book Summary : New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.

Artificial Intelligence And Machine Learning For Business Book PDF
✏Book Title : Artificial Intelligence and Machine Learning for Business
✏Author : Oliver Tensor
✏Publisher : Smart Creative Publishing
✏Release Date : 2020-10-17
✏Pages : 122
✏ISBN : 191406710X
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Artificial Intelligence and Machine Learning for Business Book Summary : 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.

Data Mining And Machine Learning In Cybersecurity Book PDF
✏Book Title : Data Mining and Machine Learning in Cybersecurity
✏Author : Sumeet Dua
✏Publisher : CRC Press
✏Release Date : 2016-04-19
✏Pages : 256
✏ISBN : 9781439839430
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Data Mining and Machine Learning in Cybersecurity Book Summary : With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and journals focus on the fragmented research topics in this area, there has been no single interdisciplinary resource on past and current works and possible

Data Mining And Knowledge Discovery With Evolutionary Algorithms Book PDF
✏Book Title : Data Mining and Knowledge Discovery with Evolutionary Algorithms
✏Author : Alex A. Freitas
✏Publisher : Springer Science & Business Media
✏Release Date : 2013-11-11
✏Pages : 265
✏ISBN : 9783662049235
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Data Mining and Knowledge Discovery with Evolutionary Algorithms Book Summary : This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics

Principles And Theory For Data Mining And Machine Learning Book PDF
✏Book Title : Principles and Theory for Data Mining and Machine Learning
✏Author : Bertrand Clarke
✏Publisher : Springer Science & Business Media
✏Release Date : 2009-07-21
✏Pages : 786
✏ISBN : 9780387981352
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Principles and Theory for Data Mining and Machine Learning Book Summary : Extensive treatment of the most up-to-date topics Provides the theory and concepts behind popular and emerging methods Range of topics drawn from Statistics, Computer Science, and Electrical Engineering

Advances In Artificial Intelligence And Data Engineering Book PDF
✏Book Title : Advances in Artificial Intelligence and Data Engineering
✏Author : Niranjan N. Chiplunkar
✏Publisher : Springer Nature
✏Release Date : 2020-08-13
✏Pages : 1475
✏ISBN : 9789811535147
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Advances in Artificial Intelligence and Data Engineering Book Summary : This book presents selected peer-reviewed papers from the International Conference on Artificial Intelligence and Data Engineering (AIDE 2019). The topics covered are broadly divided into four groups: artificial intelligence, machine vision and robotics, ambient intelligence, and data engineering. The book discusses recent technological advances in the emerging fields of artificial intelligence, machine learning, robotics, virtual reality, augmented reality, bioinformatics, intelligent systems, cognitive systems, computational intelligence, neural networks, evolutionary computation, speech processing, Internet of Things, big data challenges, data mining, information retrieval, and natural language processing. Given its scope, this book can be useful for students, researchers, and professionals interested in the growing applications of artificial intelligence and data engineering.

📒Predictive Analytics ✍ Dursun Delen

Predictive Analytics Book PDF
✏Book Title : Predictive Analytics
✏Author : Dursun Delen
✏Publisher : FT Press Analytics
✏Release Date : 2020-10-30
✏Pages : 350
✏ISBN : 0136738516
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Predictive Analytics Book Summary : In Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for students. Using predictive analytics techniques, students can uncover hidden patterns and correlations in their data, and leverage this insight to improve a wide range of business decisions. Delen's holistic approach covers all this, and more: Data mining processes, methods, and techniques The role and management of data Predictive analytics tools and metrics Techniques for text and web mining, and for sentiment analysis Integration with cutting-edge Big Data approaches Throughout, Delen promotes understanding by presenting numerous conceptual illustrations, motivational success stories, failed projects that teach important lessons, and simple, hands-on tutorials that set this guide apart from competitors.

Computational Intelligence In Data Mining Book PDF
✏Book Title : Computational Intelligence in Data Mining
✏Author : Giacomo Della Riccia
✏Publisher : Springer
✏Release Date : 2014-05-04
✏Pages : 166
✏ISBN : 9783709125885
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Computational Intelligence in Data Mining Book Summary : 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 Mining And Machine Learning For Reverse Engineering Book PDF
✏Book Title : Data Mining and Machine Learning for Reverse Engineering
✏Author : Honghui Ding
✏Publisher :
✏Release Date : 2019
✏Pages :
✏ISBN : OCLC:1190697019
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Data Mining and Machine Learning for Reverse Engineering Book Summary : "Reverse engineering is fundamental for understanding the inner workings of new malware, exploring new vulnerabilities in existing systems, and identifying patent infringements in the distributed executables. It is the process of getting an in-depth understanding of a given binary executable without its corresponding source code. Reverse engineering is a manually intensive and time-consuming process that relies on a thorough understanding of the full development stack from hardware to applications. It requires a much steeper learning curve than programming. Given the unprecedentedly vast amount of data to be analyzed and the significance of reverse engineering, the overall question that drives the studies in this thesis is how can data mining and machine learning technologies make cybersecurity practitioners more productive to uncover the provenance, understand the intention, and discover the issues behind the data in a scalable way. In this thesis, I focus on two data-driven solutions to help reverse engineers analyzing binary data: assembly clone search and behavioral summarization. Assembly code clone search is emerging as an Information Retrieval (IR) technique that helps address security problems. It has been used for differing binaries to locate the changed parts, identifying known library functions such as encryption, searching for known programming bugs or zero-day vulnerabilities in existing software or Internet of Things (IoT) devices firmware, as well as detecting software plagiarism or GNU license infringements when the source code is unavailable. However, designing an effective search engine is difficult, due to varieties of compiler optimization and obfuscation techniques that make logically similar assembly functions appear to be dramatically different. By working closely with reverse engineers, I identify three different scenarios of reverse engineering and develop novel data mining and machine learning models for assembly clone search to address the respective challenges. By developing an intelligent assembly clone search platform, I optimize the process of reverse engineering by addressing the information needs of reverse engineers. Experimental results suggest that Kam1n0 is accurate, efficient, and scalable for handling a large volume of data.The second part of the thesis goes beyond optimizing an information retrieval process for reverse engineering. I propose to automatically and statically characterize the behaviors of a given binary executable. Behavioral indicators denote those potentially high-risk malicious behaviors exhibited by malware, such as unintended network communications, file encryption, keystroke logging, abnormal registry modifications, sandbox evasion, and camera manipulation. I design a novel neural network architecture that models the different aspects of an executable. It is able to predict over 139 suspicious and malicious behavioral indicators, without running the executable. The resulting system can be used as an additional binary analytic layer to mitigate the issues of polymorphism, metamorphism, and evasive techniques. It also provides another behavioral abstraction of malware to security analysts and reverse engineers. Therefore, it can reduce the data to be manually analyzed, and the reverse engineers can focus on the binaries that are of their interest. In summary, this thesis presents four original research projects that not only advance the knowledge in reverse engineering and data mining, but also contribute to the overall safety of our cyber world by providing open-source award-winning binary analysis systems that empower cybersecurity practitioners"--

Statistical And Machine Learning Data Mining  Book PDF
✏Book Title : Statistical and Machine Learning Data Mining
✏Author : Bruce Ratner
✏Publisher : CRC Press
✏Release Date : 2017-07-12
✏Pages : 662
✏ISBN : 9781351652384
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Statistical and Machine Learning Data Mining Book Summary : Interest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. In the third edition of this bestseller, the author has completely revised, reorganized, and repositioned the original chapters and produced 13 new chapters of creative and useful machine-learning data mining techniques. In sum, the 43 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. What is new in the Third Edition: The current chapters have been completely rewritten. The core content has been extended with strategies and methods for problems drawn from the top predictive analytics conference and statistical modeling workshops. Adds thirteen new chapters including coverage of data science and its rise, market share estimation, share of wallet modeling without survey data, latent market segmentation, statistical regression modeling that deals with incomplete data, decile analysis assessment in terms of the predictive power of the data, and a user-friendly version of text mining, not requiring an advanced background in natural language processing (NLP). Includes SAS subroutines which can be easily converted to other languages. As in the previous edition, this book offers detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. The author addresses each methodology and assigns its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.

Integration Challenges For Analytics Business Intelligence And Data Mining Book PDF
✏Book Title : Integration Challenges for Analytics Business Intelligence and Data Mining
✏Author : Azevedo, Ana
✏Publisher : IGI Global
✏Release Date : 2020-12-11
✏Pages : 250
✏ISBN : 9781799857839
✏Available Language : English, Spanish, And French

Click Here To Get Book

✏Integration Challenges for Analytics Business Intelligence and Data Mining Book Summary : 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.