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Understanding Machine Learning
Machine learning (ML) is a subfield of Al that allows computers to "self-learn" from data sets without being specifically designed for this purpose. Algorithms that use machine learning can analyse data and figure out what to expect in the future based on what they've learned. In a nutshell, algorithms and models used in machine learning acquire knowledge via repetition and experimentation. Traditional programming entails a computer engineer writing a set of instructions for a computer to follow in order to convert a given set of input data into a specified set of output data. Most commands follow an IF-THEN format: the computer does something when a given condition is satisfied. Yet, comput...
Deep Learning: Fundamentals, Theory and Applications
More complex computing approaches have grown in popularity as technology has improved and big data has emerged. Increasing customer demand for better goods, as well as firms trying to better exploit their resources, have been driving this trend. Machine learning is a field that combines statistics, mathematics, and computer science to create and analyze algorithms that improve their own behavior in an iterative fashion by design. Initially, the discipline was committed to the development of artificial intelligence, but owing to the constraints of theory and technology at the time, it became more reasonable to concentrate these algorithms on particular tasks. Deep learning is a sort of machin...
Data Mining: Concepts and Techniques
Concepts and Methods for Data Mining offer the framework for understanding and using the methods for analyzing data or information for usage in a range of contexts. Data mining is defined, along with the methods and software used to extract insights from large datasets. The term "knowledge discovery from data" (KDD) is used to describe the content of this book. It examines the practicality, utility, efficiency, and scalability of methods for handling massive data volumes. This new version begins with a description of data mining and then moves on to techniques for discovering, preprocessing, processing, and storing data. Following that, the data warehouses, OLAP, as well as data cube technologies are discussed. Then, the procedures for discovering repeating structures in huge datasets are outlined. This book explains all you need to know about data clustering and classification techniques. The subsequent chapters explore data mining's patterns, uses, and potential future directions, with a focus on outlier identification. The book is meant for readers interested in data mining, including CS students, software developers, company executives, and academics.
Database Management System – Concepts And Architectures
The book starts with an introduction that covers the fundamentals, including Database User's Database Languages, & Administrators, Database Design, as well as Data Storage, and Querying. The conceptual design, the logical design, and the physical design are the three stages that are covered in this book, which follow the conventional approach for the construction of databases. Understanding the process of researching databases and constructing databases may be made easier with the help of this technique, which is logical and organized. The content that is provided in this book has a strong focus on applications, practical problems, and implementation, in addition to providing a full discussi...
Blockchain Technology And Its Applications
Blockchain is a term that has travelled more than any other technical terms in the recent past, despite the fact that the term itself contains the word "Block" in its own name. It can be heard in practically all of the current information technology infrastructures, which indicates that it poses a possible risk to the very survival of the existing businesses. Many experts believe that blockchain is the technology of the future. This Book attempts to make things easier to grasp for everyone who is interested in learning about technological advancements. This book may serve as a starting point for anybody interested in learning more about blockchain technology. However it is important to keep ...
Basics Of Artificial Intelligence : Concepts And Applications
The goal of Artificial Intelligence (AI) is to give machines (such as computers, robots controlled by computers, and software) the ability to think intelligently, as people do. The goal of artificial intelligence (AI) is to create smart software and systems by modelling human cognitive processes including learning, decision-making, and problem-solving. This book examines the development of artificial intelligence and the ways in which it has interacted with other academic fields including philosophy, psychology, and neuroscience. It also addresses some of the difficulties researchers have encountered in trying to develop intelligent computer systems. It also focuses on planning problems and ...
Cloud Analytics for Industry 4.0
This book provides research on the state-of-the-art methods for data management in the fourth industrial revolution, with particular focus on cloud.based data analytics for digital manufacturing infrastructures. Innovative techniques and methods for secure, flexible and profitable cloud manufacturing will be gathered to present advanced and specialized research in the selected area.
Computational Intelligence for Engineering and Management Applications
This book comprises select proceedings of the 1st International Conference on Computational Intelligence for Engineering and Management Applications (CIEMA - 2022). This book emphasizes applications of computational intelligence including machine intelligence, data analytics, and optimization algorithms for solving fundamental and advanced engineering and management problems. This book serves as a valuable resource for researchers, industry professionals, academicians, and doctoral scholars in engineering, production, thermal, materials, design, computer engineering, natural sciences, and management who work on computational intelligence. The book also serves researchers who are willing to use computational intelligence algorithms in real-time applications.
Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough
This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems – theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current v...
