Machine Theory

Finance students and practitioners may ask: can machines learn everything? Could AI help me? Computing students or practitioners may ask: which of my skills could contribute to finance? Where in finance should I pay attention? This book aims to answer...

Explore the ever-growing world of genetic algorithms to solve search, optimization, and AI-related tasks, and improve machine learning models using Python libraries such as DEAP, scikit-learn, and NumPy Key Features Explore the ins and outs of genetic...

A computational perspective on partial order and lattice theory, focusing on algorithms and their applications This book provides a uniform treatment of the theory and applications of lattice theory. The applications covered include tracking dependency...

The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of...

Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman...

It seems that artificial intelligence (AI) is always just five years away, but it never arrives. Recently, however, developments have made the practical utility of game theory a genuine reality. Will sport provide the petri dish in which AI will prove...

Now that storage and collection technologies are cheaper and more precise, methods for extracting relevant information from large datasets is within the reach any experienced programmer willing to crunch data. With this book, you'll learn machine...

The study of network theory is a highly interdisciplinary field, which has emerged as a major topic of interest in various disciplines ranging from physics and mathematics, to biology and sociology. This book promotes the diverse nature of the study of...

Text analytics consist of the statistics about a text element, which includes the word count, the word histogram, and the word frequency histogram. Most text documents of value are related to other—sometimes many other—documents, and so analytics...

Leverage causal inference concepts, from foundations to advanced techniques, through a practical, hands-on approach with extensive R code examples and real-world applications Key Features Explore causal analysis with hands-on R tutorials and real-world...

This book offers a gentle motivation and introduction to computational thinking, in particular to algorithms and how they can be coded to solve significant, topical problems from domains such as finance, cryptography, Web search, and data compression...

Maxim Lapan delivers intuitive explanations and insights into complex reinforcement learning (RL) concepts, starting from the basics of RL on simple environments and tasks to modern, state-of-the-art methods Purchase of the print or Kindle book...

Learn traditional and cutting-edge machine learning (ML) and deep learning techniques and best practices for time series forecasting, including global forecasting models, conformal prediction, and transformer architectures Key Features Apply ML and...

An urgent book on generative artificial intelligence exploring the risk and benefits looming in this seminal moment'Easily the best exploration to date on the perils and promise of AI." -ASHLEE VANCE author of When the Heavens Went on Sale'Mastering AI...

The book essentially covers the growing role of AI in the oil and gas industry, including digital technologies used in the exploration phase, customer sales service, and cloud-based digital storage of reservoir simulation data for modeling. It starts...

The Lanczos Method: Evolution and Application is divided into two distinct parts. The first part reviews the evolution of one of the most widely used numerical techniques in the industry. The development of the method, as it became more robust, is...

Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or functional approximation. This volume presents methods for the study of approximate iterative algorithms, providing...

In this book, we have set up a unified analytical framework for various human-robot systems, which involve peer-peer interactions (either space-sharing or time-sharing) or hierarchical interactions. A methodology in designing the robot behavior through...

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource:Addresses nearest-neighbor-based,...

The First International Conference on Signal and Information Processing, Networking and Computers (ICSINC) focuses on the key technologies and challenges of signal and information processing schemes, network application, computer theory and application,...

This book covers the different technologies of Internet, and machine learning capabilities involved in Cognitive Internet of Things (CIoT). Machine learning is explored by covering all the technical issues and various models used for data analytics...

In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications...

Modern Directional Statistics collects important advances in methodology and theory for directional statistics over the last two decades. It provides a detailed overview and analysis of recent results that can help both researchers and practitioners...

This book covers the state-of-art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy machine learning and deep learning algorithms. Both types of algorithms are described in such...

Most biometric books are either extraordinarily technical for technophiles or extremely elementary for the lay person. Striking a balance between the two, Biometric Technology: Authentication, Biocryptography, and Cloud-Based Architecture is ideal for...

Artificial Intelligence in Information and Communication Technologies, Healthcare and Education: A Roadmap Ahead is designed as a reference text and discusses inter-dependability, communication and effective control for the betterment of services through...

A general class of powerful and flexible modeling techniques, spline smoothing has attracted a great deal of research attention in recent years and has been widely used in many application areas, from medicine to economics. Smoothing Splines: Methods and...

With the advancement of statistical methodology inextricably linked to the use of computers, new methodological ideas must be translated into usable code and then numerically evaluated relative to competing procedures. In response to this, Statistical...

While mathematical software packages are commercially successful and widely used, the use of formal methods in hardware and software development is also becoming more and more important and necessary. This has made deduction systems indispensable because...

Coefficient of Variation (CV) is a unit free index indicating the consistency of the data associated with a real-world process and is simple to mold into computational paradigms. This book provides necessary exposure of computational strategies,...

The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others. At the root of these techniques...

Swarm Intelligence: Principles, Advances, and Applications delivers in-depth coverage of bat, artificial fish swarm, firefly, cuckoo search, flower pollination, artificial bee colony, wolf search, and gray wolf optimization algorithms. The book begins...

This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's guide to engineers or students who want to have a quick start on learning and/or building deep learning systems...

With the ongoing release of 3D movies and the emergence of 3D TVs, 3D imaging technologies have penetrated our daily lives. Yet choosing from the numerous 3D vision methods available can be frustrating for scientists and engineers, especially without a...

The recent rapid growth in the variety and complexity of new machine learning architectures requires the development of improved methods for designing, analyzing, evaluating, and communicating machine learning technologies. Statistical Machine Learning:...

This book provides theoretical and practical knowledge on AI and swarm intelligence. It provides a methodology for EA (evolutionary algorithm)-based approach for complex adaptive systems with the integration of several meta-heuristics, e.g., ACO (Ant...

Embrace emerging AI trends and integrate your operations with cutting-edge solutions Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies...

This is a practical guide to P-splines, a simple, flexible and powerful tool for smoothing. P-splines combine regression on B-splines with simple, discrete, roughness penalties. They were introduced by the authors in 1996 and have been used in many...

This book is a history of artificial intelligence, that audacious effort to duplicate in an artifact what we consider to be our most important property-our intelligence. It is an invitation for anybody with an interest in the future of the human race to...

Learn to leverage Microsoft's new AI tool, Copilot, for enhanced productivity at work In Microsoft 365 Copilot At Work: Using AI to Get the Most from Your Business Data and Favorite Apps, a team of software and AI experts delivers a comprehensive guide...