Recent Trends in Learning From Data

Recent Trends in Learning From Data PDF Author: Luca Oneto
Publisher: Springer Nature
ISBN: 303043883X
Category : Technology & Engineering
Languages : en
Pages : 225

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Book Description
This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.

Recent Trends in Learning From Data

Recent Trends in Learning From Data PDF Author: Luca Oneto
Publisher: Springer Nature
ISBN: 303043883X
Category : Technology & Engineering
Languages : en
Pages : 225

Get Book Here

Book Description
This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.

Recent Trends in Learning From Data

Recent Trends in Learning From Data PDF Author: Luca Oneto
Publisher: Springer
ISBN: 9783030438852
Category : Technology & Engineering
Languages : en
Pages : 221

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Book Description
This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.

Recent Trends and Future Challenges in Learning from Data

Recent Trends and Future Challenges in Learning from Data PDF Author: Cristina Davino
Publisher: Springer Nature
ISBN: 3031544684
Category :
Languages : en
Pages : 158

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Book Description


Learning from Data

Learning from Data PDF Author: Yaser S. Abu-Mostafa
Publisher:
ISBN: 9781600490064
Category : Machine learning
Languages : en
Pages : 201

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Book Description


Learning from Data

Learning from Data PDF Author: Vladimir Cherkassky
Publisher: John Wiley & Sons
ISBN: 9780470140512
Category : Computers
Languages : en
Pages : 560

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Book Description
An interdisciplinary framework for learning methodologies—covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied—showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.

Handbook of Research on Emerging Trends and Applications of Machine Learning

Handbook of Research on Emerging Trends and Applications of Machine Learning PDF Author: Solanki, Arun
Publisher: IGI Global
ISBN: 1522596453
Category : Computers
Languages : en
Pages : 674

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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.

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches PDF Author: K. Gayathri Devi
Publisher: CRC Press
ISBN: 1000179516
Category : Computers
Languages : en
Pages : 267

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Book Description
Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems. The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications. Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems. Features Includes AI-based decision-making approaches Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images Covers automation of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining for decision-support applications Offers case-based reasoning

Recent Trends in Data Science and Soft Computing

Recent Trends in Data Science and Soft Computing PDF Author: Faisal Saeed
Publisher: Springer
ISBN: 3319990071
Category : Technology & Engineering
Languages : en
Pages : 1133

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Book Description
This book presents the proceedings of the 3rd International Conference of Reliable Information and Communication Technology 2018 (IRICT 2018), which was held in Kuala Lumpur, Malaysia, on July 23–24, 2018. The main theme of the conference was “Data Science, AI and IoT Trends for the Fourth Industrial Revolution.” A total of 158 papers were submitted to the conference, of which 103 were accepted and considered for publication in this book. Several hot research topics are covered, including Advances in Data Science and Big Data Analytics, Artificial Intelligence and Soft Computing, Business Intelligence, Internet of Things (IoT) Technologies and Applications, Intelligent Communication Systems, Advances in Computer Vision, Health Informatics, Reliable Cloud Computing Environments, Recent Trends in Knowledge Management, Security Issues in the Cyber World, and Advances in Information Systems Research, Theories and Methods.

Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics

Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics PDF Author: Haruna Chiroma
Publisher: Springer Nature
ISBN: 3030662888
Category : Technology & Engineering
Languages : en
Pages : 316

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Book Description
This book addresses theories and empirical procedures for the application of machine learning and data mining to solve problems in cyber dynamics. It explains the fundamentals of cyber dynamics, and presents how these resilient algorithms, strategies, techniques can be used for the development of the cyberspace environment such as: cloud computing services; cyber security; data analytics; and, disruptive technologies like blockchain. The book presents new machine learning and data mining approaches in solving problems in cyber dynamics. Basic concepts, related work reviews, illustrations, empirical results and tables are integrated in each chapter to enable the reader to fully understand the concepts, methodology, and the results presented. The book contains empirical solutions of problems in cyber dynamics ready for industrial applications. The book will be an excellent starting point for postgraduate students and researchers because each chapter is design to have future research directions.

Trends of Data Science and Applications

Trends of Data Science and Applications PDF Author: Siddharth Swarup Rautaray
Publisher: Springer Nature
ISBN: 9813368152
Category : Computers
Languages : en
Pages : 341

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Book Description
This book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 7–10, 2021. The book covers contributions ranging from theoretical and foundation research, platforms, methods, applications, and tools in all areas. It provides theory and practices in the area of data science, which add a social, geographical, and temporal dimension to data science research. It also includes application-oriented papers that prepare and use data in discovery research. This book contains chapters from academia as well as practitioners on big data technologies, artificial intelligence, machine learning, deep learning, data representation and visualization, business analytics, healthcare analytics, bioinformatics, etc. This book is helpful for the students, practitioners, researchers as well as industry professional.