Machine learning

The book will focus on the applications of machine learning for sustainable development.

This book introduces empirical methods for machine learning with a special focus on applications in natural language processing (NLP) and data science.

This book introduces empirical methods for machine learning with a special focus on applications in natural language processing (NLP) and data science.

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.

The two-volume set LNBI 11465 and LNBI 11466 constitutes the proceedings of the 7th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2019, held in Granada, Spain, in May 2019.

In this book, innovative research using artificial neural networks (ANNs) is conducted to automate the placement task in analog integrated circuit layout design, by creating a generalized model that can generate valid layouts at push-button speed.

An example-rich guide for beginners to start their reinforcement and deep reinforcement learning journey with state-of-the-art distinct algorithmsKey FeaturesCovers a vast spectrum of basic-to-advanced RL algorithms with mathematical explanations of each algorithmLearn how to implement algorithms with code by following examples with line-by-line explanationsExplore the latest RL methodologies such as DDPG, PPO, and the use of expert demonstrationsBook DescriptionWith significant enhancements in the quality and quantity of algorithms in recent years, this second edition of Hands-On Reinforcement Learning with Python has been revamped into an example-rich guide to learning state-of-the-art reinforcement learning (RL) and deep RL algorithms with TensorFlow 2 and the OpenAI Gym toolkit.

Unlock the world of data science—no coding required.

This book includes the results from the 5th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR), held in National Institute of Technology, Kurukshetra, on December 07-09, 2023, which brought together visionaries, researchers, and industry leaders at the forefront of technological innovation.

Focusing on the fundamentals of machine learning, this book covers broad areas of data-driven modeling, ranging from simple regression to advanced machine learning and optimization methods for applications in materials modeling and discovery.

This updated second edition offers a guided tour of machine learning algorithms and architecture design.

Gain a thorough understanding of supervised learning algorithms by developing use cases with Python.

Bring together machine learning (ML) and deep learning (DL) in financial trading, with an emphasis on investment management.

Work with natural language tools and techniques to solve real-world problems.

Know how to adapt quantum computing and machine learning algorithms.

Large language models (LLMs) and generative AI are rapidly changing the healthcare industry.

Decision Support Systems (DSSs) are Software and Information Systems which make use of various data and business models, employ advanced data analytics procedures, and access extensive databases and data warehouses to facilitate with a decision process or with organizational issues.

This book offers both theoretical insights and hands-on experience in understanding and building machine learning-based Network Traffic Monitoring and Analysis (NTMA) and Video Quality Assessment (VQA) applications using JavaScript.

The surging predictive analytics market is expected to grow from $10.

This book is to explore and explain the strategically sound capabilities at the synchronization between quantum computing and artificial intelligence (AI).

Artificial Intelligence (AI) has been an exciting field of study and research in educational institutions and research labs across the globe.

The first edition of this textbook was published in 2021.

This book is your comprehensive guide to creating powerful, end-to-end deep learning workflows on Amazon Web Services (AWS).

Stable Diffusion, ChatGPT, Whisper - these are just a few examples of incredible applications powered by developments in machine learning.

This book introduces approaches to generalize the benefits of equivariant deep learning to a broader set of learned structures through learned homomorphisms.

The book covers a wide topic collection starting from essentials of Computational Intelligence to advance, and possible application types against COVID-19 as well as its effects on the field of medical, social, and different data-oriented research scopes.

This book explores the use of advanced geospatial techniques in geomorphic hazards modelling and risk reduction.

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising.

This edited book provides an optimal portrayal of the principles and applications related to network security.

As perception stands for the acquisition of a real world representation by interaction with an environment, learning is the modification of this internal representation.

Evolutionary computation is the study of computational systems which use ideas and get inspiration from natural evolution and adaptation.

Learning and planning are two important topics of artificial intelligence.

In recent years, a great number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems.

An autonomous agent is a computational system that acquires sensory data from its environment and decides by itself how to relate the external stimulus to its behaviors in order to attain certain goals.

This volume gathers lectures by 8 distinguished pioneers of automata theory, including two Turing Award winners.

This book focuses on Least Squares Support Vector Machines (LS-SVMs) which are reformulations to standard SVMs.

Machine learning deals with the issue of how to build computer programs that improve their performance at some tasks through experience.

In recent years, the support vector machine (SVM), a new data processing method, has been applied to many fields of chemistry and chemical technology.

Inspired by the Darwinian framework of evolution through natural selection and adaptation, the field of evolutionary computation has been growing very rapidly, and is today involved in many diverse application areas.

This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data.

This book covers a wide range of subjects in applying machine learning approaches for bioinformatics projects.

This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling.

The QL&SC 2012 is a major symposium for scientists, and practitioners all around the world to present their latest researches, results, ideas, developments and applications in such areas as quantitative logic, many-valued logic, fuzzy logic, quantification of software, artificial intelligence, fuzzy sets and systems and soft computing.

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising.

This book chronicles a 10-year introduction of blended learning into the delivery at a leading technological university, with a longstanding tradition of technology-enabled teaching and learning, and state-of-the-art infrastructure.