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Artificial Intelligence in Data Mining

Artificial Intelligence in Data Mining
  • Author : D. Binu
  • Publsiher : Academic Press
  • Release : 01 May 2021
  • ISBN : 0128206160
  • Pages : 270 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKArtificial Intelligence in Data Mining

Summary:
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 in Data Mining

Artificial Intelligence in Data Mining
  • Author : D. Binu,B.R. Rajakumar
  • Publisher : Academic Press
  • Release : 01 May 2021
GET THIS BOOKArtificial Intelligence in Data Mining

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


Machine Learning and Data Mining

Machine Learning and Data Mining
  • Author : Igor Kononenko,Matjaz Kukar
  • Publisher : Horwood Publishing
  • Release : 14 May 2007
GET THIS BOOKMachine Learning and Data Mining

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. Written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining, this text is suitable foradvanced undergraduates, postgraduates and tutors in a wide area of computer science and technology, as well as


Machine Learning and Data Mining in Aerospace Technology

Machine Learning and Data Mining in Aerospace Technology
  • Author : Aboul Ella Hassanien,Ashraf Darwish,Hesham El-Askary
  • Publisher : Springer
  • Release : 16 July 2019
GET THIS BOOKMachine Learning and Data Mining in Aerospace Technology

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


Programming Collective Intelligence

Programming Collective Intelligence
  • Author : Toby Segaran
  • Publisher : "O'Reilly Media, Inc."
  • Release : 16 August 2007
GET THIS BOOKProgramming Collective Intelligence

Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes


Introduction to Algorithms for Data Mining and Machine Learning

Introduction to Algorithms for Data Mining and Machine Learning
  • Author : Xin-She Yang
  • Publisher : Academic Press
  • Release : 15 July 2019
GET THIS BOOKIntroduction to Algorithms for Data Mining and Machine Learning

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


Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition
  • Author : Petra Perner
  • Publisher : Springer
  • Release : 19 August 2018
GET THIS BOOKMachine Learning and Data Mining in Pattern Recognition

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


Data Mining and Machine Learning in Cybersecurity

Data Mining and Machine Learning in Cybersecurity
  • Author : Sumeet Dua,Xian Du
  • Publisher : CRC Press
  • Release : 19 April 2016
GET THIS BOOKData Mining and Machine Learning in Cybersecurity

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


Advances in Machine Learning and Data Mining for Astronomy

Advances in Machine Learning and Data Mining for Astronomy
  • Author : Michael J. Way,Jeffrey D. Scargle,Kamal M. Ali,Ashok N. Srivastava
  • Publisher : CRC Press
  • Release : 29 March 2012
GET THIS BOOKAdvances in Machine Learning and Data Mining for Astronomy

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



Encyclopedia of Machine Learning

Encyclopedia of Machine Learning
  • Author : Claude Sammut,Geoffrey I. Webb
  • Publisher : Springer Science & Business Media
  • Release : 28 March 2011
GET THIS BOOKEncyclopedia of Machine Learning

This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.



Machine Learning and Data Mining for Computer Security

Machine Learning and Data Mining for Computer Security
  • Author : Marcus A. Maloof
  • Publisher : Springer Science & Business Media
  • Release : 28 February 2006
GET THIS BOOKMachine Learning and Data Mining for Computer Security

"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


Data Mining: Practical Machine Learning Tools and Techniques

Data Mining: Practical Machine Learning Tools and Techniques
  • Author : Ian H. Witten,Eibe Frank,Mark A. Hall
  • Publisher : Elsevier
  • Release : 03 February 2011
GET THIS BOOKData Mining: Practical Machine Learning Tools and Techniques

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


Think Bayes

Think Bayes
  • Author : Allen Downey
  • Publisher : "O'Reilly Media, Inc."
  • Release : 12 September 2013
GET THIS BOOKThink Bayes

If you know how to program with Python and also know a little about probability, you’re ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you’ll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more


Data Mining

Data Mining
  • Author : Ian H. Witten,Eibe Frank
  • Publisher : Elsevier
  • Release : 13 July 2005
GET THIS BOOKData Mining

Data Mining, Second Edition, describes data mining techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights of this new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information