The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty.
This book highlights recent advances in computational intelligence for signal processing, computing, imaging, artificial intelligence, and their applications.
This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics.
This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data.
This book provides a collection of selected papers presented at the International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2019), which was held in Goa, India, on 16-17 August 2019.
Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the most compelling areas of computer science research.
This book presents machine learning as a set of pre-requisites, co-requisites, and post-requisites, focusing on mathematical concepts and engineering applications in advanced welding and cutting processes.
Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the most compelling areas of computer science research.
This book aims to solve some key problems in the decision and optimization procedure for power market organizers and participants in data-driven approaches.
The book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone, for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning.
This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives - the statistical perspective, the artificial neural network perspective and the deep learning methodology.
This set of lecture notes, written for those who are unfamiliar with mathematics and programming, introduces the reader to important concepts in the field of machine learning.
This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering.
This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applications.
This edited book is a collection of selected research papers presented at the 2022 3rd International Conference on Artificial Intelligence in Education Technology (AIET 2022), held in Wuhan, China, on July 1-3, 2022.
Los investigadores, estudiantes o profesionales de la industria involucrados en temas de Aprendizaje Automático encontrarán en este libro una referencia de base sobre las tecnologías teórico-prácticas más avanzadas en dicho campo, proporcionadas por los diecinueve autores que han unido sus esfuerzos y elaborado sus contenidos.
Generative adversarial networks (GANs) were introduced by Ian Goodfellow and his co-authors including Yoshua Bengio in 2014, and were to referred by Yann Lecun (Facebook's AI research director) as "e;the most interesting idea in the last 10 years in ML.
Human Cognition and Social Agent Technology is written for readers who are curious about what human (social) cognition is, and whether and how advanced software programs or robots can become social agents.
Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner.
This book builds on the success of "e;Working to Learn"e; (Palgrave Macmillan, 2020) by focusing on the future of work and how young people, especially low-income young people and young people of color, are pursuing college and career goals through work-based learning experiences, yet encountering an increasingly racially and socioeconomically stratified labor market and educational system.
Affective Computing for Social Good: Enhancing Well-being, Empathy, and Equity offers an insightful journey into the intricate realm of affective computing.
Affective Computing for Social Good: Enhancing Well-being, Empathy, and Equity offers an insightful journey into the intricate realm of affective computing.
This book delves into a broad spectrum of topics, covering the foundational aspects of Large Language Models (LLMs) such as PaLM, LLaMA, BERT, and GPT, among others.
Applications of Machine Learning in Hydroclimatology is a comprehensive exploration of the transformative potential of machine learning for addressing critical challenges in water resources management.
The book Applied Artificial Intelligence 2: Medicine, Biology, Chemistry, Financial, Games, Engineering is providing exceptional chapters of the state-of-the-art research knowledge and results on the innovative theories, methodology and applications of artificial intelligence and its sub-domain like deep learning, machine learning in different areas such as medicine, economy, education, law, smart city, government, industry etc.
The book Applied Artificial Intelligence 2: Medicine, Biology, Chemistry, Financial, Games, Engineering is providing exceptional chapters of the state-of-the-art research knowledge and results on the innovative theories, methodology and applications of artificial intelligence and its sub-domain like deep learning, machine learning in different areas such as medicine, economy, education, law, smart city, government, industry etc.
This book provides an extensive examination of state-of-the-art methods in multimodal retrieval, generation, and the pioneering field of retrieval-augmented generation.
This text presents a collection of mathematical exercises with the aim of guiding readers to study topics in statistical physics, equilibrium thermodynamics, information theory, and their various connections.
