Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository.
Event-Triggered and Time-Triggered Control Paradigms presents a valuable survey about existing architectures for safety-critical applications and discusses the issues that must be considered when moving from a federated to an integrated architecture.
Innovation in Manufacturing Networks A fundamental concept of the emergent business, scientific and technological paradigms ces area, innovation the ability to apply new ideas to products, processes, organizational practices and business models - is crucial for the future competitiveness of organizations in a continually increasingly globalised, knowledge-intensive marketplace.
Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncertain data mining field in a structured and concise way.
AI Computing Systems: An Application Driven Perspective adopts the principle of "e;application-driven, full-stack penetration"e; and uses the specific intelligent application of "e;image style migration"e; to provide students with a sound starting place to learn.
Blockchain Technology for Emerging Applications: A Comprehensive Approach explores recent theories and applications of the execution of blockchain technology.
The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations.
Perspectives in Artificial Intelligence, Volume 1: Case-Based Planning: Viewing Planning as a Memory Task focuses on the processes, methodologies, and techniques employed in viewing planning as a memory task.
A practical syllabus-based UiPath Associate certification guide to confidently passing your UiPath RPA Associate certification examination, covering real-world business cases, mock tests, and moreKey FeaturesGet certified successfully with this detailed syllabus-oriented examination guideWork with real-world business cases that will help you grasp RPA topics better using practical examplesPractice with quizzes and mock exam papers with answers to prepare for the exam confidentlyBook DescriptionUiPath is the most popular vendor in the Robotic Process Automation (RPA) industry.
Get to grips with automated machine learning and adopt a hands-on approach to AutoML implementation and associated methodologiesKey FeaturesGet up to speed with AutoML using OSS, Azure, AWS, GCP, or any platform of your choiceEliminate mundane tasks in data engineering and reduce human errors in machine learning modelsFind out how you can make machine learning accessible for all users to promote decentralized processesBook DescriptionEvery machine learning engineer deals with systems that have hyperparameters, and the most basic task in automated machine learning (AutoML) is to automatically set these hyperparameters to optimize performance.
Tackle the complex challenges faced while building end-to-end deep learning models using modern R librariesKey FeaturesUnderstand the intricacies of R deep learning packages to perform a range of deep learning tasksImplement deep learning techniques and algorithms for real-world use casesExplore various state-of-the-art techniques for fine-tuning neural network modelsBook DescriptionDeep learning (DL) has evolved in recent years with developments such as generative adversarial networks (GANs), variational autoencoders (VAEs), and deep reinforcement learning.
Make your searches more responsive and smarter by applying Artificial Intelligence to itKey FeaturesEnter the world of Artificial Intelligence with solid concepts and real-world use casesMake your applications intelligent using AI in your day-to-day apps and become a smart developerDesign and implement artificial intelligence in searchesBook DescriptionWith the emergence of big data and modern technologies, AI has acquired a lot of relevance in many domains.
Build a strong and efficient IoT infrastructure at industrial and enterprise level by mastering Industrial IoT network Key FeaturesGain hands-on experience working with industrial architectureExplore the potential of cloud-based Industrial IoT platforms, analytics, and protocolsImprove business models and transform your workforce with Industry 4.
The advancement of biomedical engineering has enabled the generation of multi-omics data by developing high-throughput technologies, such as next-generation sequencing, mass spectrometry, and microarrays.
This text covers all of the data science, machine learning, and deep learning topics relevant to materials science and engineering, accompanied by numerous examples and applications.
Evolution of Knowledge Science: Myth to Medicine: Intelligent Internet-Based Humanist Machines explains how to design and build the next generation of intelligent machines that solve social and environmental problems in a systematic, coherent, and optimal fashion.
The promises and realities of digital innovation have come to suffuse everything from city regions to astronomy, government to finance, art to medicine, politics to warfare, and from genetics to reality itself.
Evolution of Knowledge Science: Myth to Medicine: Intelligent Internet-Based Humanist Machines explains how to design and build the next generation of intelligent machines that solve social and environmental problems in a systematic, coherent, and optimal fashion.
The complexity of most real-time and embedded systems often exceeds that of other types of systems since, in addition to the usual spectrum of problems inherent in software, they need to deal with the complexities of the physical world.
As the number of processor cores and IP blocks integrated on a single chip is steadily growing, a systematic approach to design the communication infrastructure becomes necessary.
Jump Time-Delay Systems (JTDS) represent a new class of piece-wise deterministic systems, in which the underlying dynamics is governed by delay-differential equations and it possesses multiple modes of operation depending on the value of an associated Markov random process.
In recent years, tremendous research has been devoted to the design of database systems for real-time applications, called real-time database systems (RTDBS), where transactions are associated with deadlines on their completion times, and some of the data objects in the database are associated with temporal constraints on their validity.
Most everything in our experience requires management in some form or other: our gardens, our automobiles, our minds, our bodies, our love lives, our businesses, our forests, our countries, etc.
A large international conference on Advances in Machine Learning and Data Analysis was held in UC Berkeley, California, USA, October 22-24, 2008, under the auspices of the World Congress on Engineering and Computer Science (WCECS 2008).
The three volume proceedings LNAI 10534 - 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017.
UML for Developing Knowledge Management Systems provides knowledge engineers the framework in which to identify types of knowledge and where this knowledge exists in an organization.
In this much anticipated sequel to the legal bestseller, The Future of Law, Susskind lays down a challenge to all lawyers to ask themselves, with their hands on their hearts, what elements of their current workload could be undertaken differently - more quickly, cheaply, efficiently, or to a higher quality - using alternative methods of working.
In this book Haridimos Tsoukas, one of the most imaginative organization theorists of our time, examines the nature of knowledge in organizations, and how individuals and scholars approach the concept of knowledge.
The four-volume set LNCS 11746-11749 constitutes the proceedings of the 17th IFIP TC 13 International Conference on Human-Computer Interaction, INTERACT 2019, held in Paphos, Cyprus, in September 2019.
Distributed Computing by Mobile Entities is concerned with the study of the computational and complexity issues arising in systems of decentralized computational entities operating in a spatial universe Encompassing and modeling a large variety of application environments and systems, from robotic swarms to networks of mobile sensors, from software mobile agents in communication networks to crawlers and viruses on the web, the theoretical research in this area intersects distributed computing with the fields of computational geometry (especially for continuous spaces), control theory, graph theory and combinatorics (especially for discrete spaces).
In this much anticipated sequel to the legal bestseller, The Future of Law, Susskind lays down a challenge to all lawyers to ask themselves, with their hands on their hearts, what elements of their current workload could be undertaken differently - more quickly, cheaply, efficiently, or to a higher quality - using alternative methods of working.
Discover expert techniques for combining machine learning with the analytic capabilities of Elastic Stack and uncover actionable insights from your dataKey FeaturesIntegrate machine learning with distributed search and analyticsPreprocess and analyze large volumes of search data effortlesslyOperationalize machine learning in a scalable, production-worthy wayBook DescriptionElastic Stack, previously known as the ELK stack, is a log analysis solution that helps users ingest, process, and analyze search data effectively.
In this book Haridimos Tsoukas, one of the most imaginative organization theorists of our time, examines the nature of knowledge in organizations, and how individuals and scholars approach the concept of knowledge.