Machine Learning: Concepts, Methodologies, Tools and Applications PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Machine Learning: Concepts, Methodologies, Tools and Applications PDF full book. Access full book title Machine Learning: Concepts, Methodologies, Tools and Applications by Management Association, Information Resources. Download full books in PDF and EPUB format.
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1609608194
Category : Computers
Languages : en
Pages : 2174
Get Book Here
Book Description
"This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1609608194
Category : Computers
Languages : en
Pages : 2174
Get Book Here
Book Description
"This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe
Author: Wolfgang Kreutzer
Publisher: Addison Wesley Publishing Company
ISBN:
Category : Computers
Languages : en
Pages : 704
Get Book Here
Book Description
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 152251760X
Category : Computers
Languages : en
Pages : 3095
Get Book Here
Book Description
Ongoing advancements in modern technology have led to significant developments in artificial intelligence. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Artificial Intelligence: Concepts, Methodologies, Tools, and Applications provides a comprehensive overview of the latest breakthroughs and recent progress in artificial intelligence. Highlighting relevant technologies, uses, and techniques across various industries and settings, this publication is a pivotal reference source for researchers, professionals, academics, upper-level students, and practitioners interested in emerging perspectives in the field of artificial intelligence.
Author: Dr.S.Alex David
Publisher: SK Research Group of Companies
ISBN: 9364920309
Category : Computers
Languages : en
Pages : 204
Get Book Here
Book Description
Dr.S.Alex David, Professor and Head, Department of Artificial Intelligence and Machine Learning, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India. Dr.N.K.Manikandan, Assistant Professor (Senior Grade), Department of Computer Science & Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India. Mrs.Hemalatha D, Assistant Professor, Department of Computer Science & Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India. Dr.Almas Begum, Professor, Department of Computer Science & Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India.
Author: Hong Jiao
Publisher: IAP
ISBN: 1641139536
Category : Computers
Languages : en
Pages : 218
Get Book Here
Book Description
The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased. Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers’ engagement in testing. In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices.
Author: Jorge Marx Gómez
Publisher: Springer Nature
ISBN: 3031565762
Category :
Languages : en
Pages : 273
Get Book Here
Book Description
Author: Uma N. Dulhare
Publisher: John Wiley & Sons
ISBN: 1119654742
Category : Computers
Languages : en
Pages : 544
Get Book Here
Book Description
This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
Get Book Here
Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Author: Rashmi Agrawal
Publisher: CRC Press
ISBN: 1000098281
Category : Computers
Languages : en
Pages : 339
Get Book Here
Book Description
The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools. This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them. Features Addresses the complete data science technologies workflow Explores basic and high-level concepts and services as a manual for those in the industry and at the same time can help beginners to understand both basic and advanced aspects of machine learning Covers data processing and security solutions in IoT and Big Data applications Offers adaptive, robust, scalable and reliable applications to develop solutions for day-to-day problems Presents security issues and data migration techniques of NoSQL databases
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1799824616
Category : Science
Languages : en
Pages : 1961
Get Book Here
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.
