Machine learning Books

An emerging topic in software engineering and data mining, specification mining tackles software maintenance and reliability issues that cost economies billions of dollars each year. The first unified reference on the subject, Mining Software...

Explores the evolution from Industry 4.0 to the cutting-edge Industry 6.0, offering insights into the integration of next-generation computing, including IoT, AI, machine learning, deep learning, edge computing and quantum computing.

The book provides an in-depth exploration of cutting-edge technologies and how they are used to support data-driven marketing strategies and empower organizations to make the right decisions.

This timely book affirms that humans can flourish in the Age of AI by relying on their unique strengths, and explores the skills and knowledge that are required to interact effectively, efficiently and responsibly with AIs, both today and in the future.

This book elaborates fuzzy machine and deep learning models for single class mapping from multi-sensor, multi-temporal remote sensing images while handling mixed pixels and noise. It also covers the ways of pre-processing and spectral dimensionality...

Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of natural language processing (NLP), speech, and computer vision tasks. It simplifies and...

Handbook of Artificial Intelligence Applications for Industrial Sustainability examines the influence of AI and how it can be used in several industries to improve corporate performance, reduce security concerns, improve customer experience, and...

The history of robotics and artificial intelligence in many ways is also the history of humanity's attempts to control such technologies. From the Golem of Prague to the military robots of modernity, the debate continues as to what degree of independence...

Video has rich information including meta-data, visual, audio, spatial and temporal data which can be analysed to extract a variety of low and high-level features to build predictive computational models using machine-learning algorithms to discover...

The human face is perhaps the most familiar and easily recognized object in the world, yet both its three-dimensional shape and its two-dimensional images are complex and hard to characterize. This book develops the vocabulary of ridges and parabolic...

Consider this: Robots will one day be able to write poetry and prose so touching that it will make men weep; compose dozens or even hundreds of symphonies that will rival the work of Mozart; judge a court case with absolute impartiality and fairness; or...

Metaheuristic algorithms are considered as generic optimization tools that can solve very complex problems characterized by having very large search spaces. Metaheuristic methods reduce the effective size of the search space through the use of effective...

This book was written by the architect of two MS Analytics programs and one undergraduate specialization in Business Analytics, with over a decade of experience teaching and practicing predictive analytics, and co-chairing premier academic conference...

"Get ready to unlock your full potential with ChatGPT! In this comprehensive guide, you'll discover the power of prompt engineering to boost your creativity, productivity, and effectiveness in various niches such as writing, music, business, health,...

Welcome to "Mastering Machine Learning: A Comprehensive Guide to Success." In this book, we embark on an exciting journey into the world of machine learning (ML), exploring its concepts, techniques, and practical applications. Whether you are a...

Mathematical modelling and simulation are viewed as viable alternatives to performing experiments in medicine and biology, and are discussed in this book. The book also explores the probabilistic computational deep learning model for cancer...

Author Yuxi (Hayden) Liu teaches machine learning from the fundamentals to building NLP transformers and multimodal models with best practice tips and real-world examples using PyTorch, TensorFlow, scikit-learn, and pandasKey Features:- Discover new and...

No hype or jargon-become adept at asking good questions about the data and obtaining answers to add significant business value to analytics and artificial intelligence (AI). We start by exploring fundamental topics, such as how data relates to your pain...

This book heralds a new era in instrumentation and measurements. It combines artificial intelligence and wireless communications technologies with instrumentation and measurement systems to function as a single unit.

Provides a complete and concise overview of deep learning using the language of mathematics. Provides a self-contained background on machine learning and optimization algorithms, and progresses through the key ideas of deep learning.

Searching for a needle in a haystack is an important task in several contexts of data analysis and decision-making. Examples include identifying the insider threat within an organization, the prediction of failure in industrial production or pinpointing...

The fields of Artificial Intelligence and Machine Learning have grown dramatically in recent years, with an increasingly impressive spectrum of successful applications. This book represents a key reference for anybody interested in the intersection...

What Every Engineer Should Know About Data-Driven Analytics provides a comprehensive introduction to the theoretical concepts and approaches of machine learning that are used in predictive data analytics. By introducing the theory and by providing...

torch is an R port of PyTorch, one of the two most-employed deep learning frameworks in industry and research. It is also an excellent tool to use in scientific computations. It is written entirely in R and C/C++.Though still "young" as a project, R...

This book discusses the newest approach to online learning systems in higher education. As e-Learning platforms change their mechanisms for data processing and storage, there is a need to move these systems toward being more efficient and smarter. This...

This book covers advancements and future challenges in biomedical application development using disruptive technologies like AI, IoT and Signal Processing. Book is divided into 4 main sections namely medical image processing using AI, IoT and biomedical...

Advances in Graph based Natural Language Processing (NLP) and Information Retrieval (IR) tasks have shown the importance of processing Graph of Words.

This book focuses on the futuristic approaches and designs for real-time systems and applications, as well as the fundamental concepts of including advanced techniques and tools with the models of the data-driven blockchain ecosystem.

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment...

This book offers a complete assessment of the present scenario, role, challenges, technologies, and impact of IoMT-enabled smart healthcare systems. It contains chapters discussing various biomedical applications under the umbrella of the IoMT.

This book highlights various evolutionary algorithm techniques for various medical conditions and introduces medical applications of evolutionary computation for real-time diagnosis.

Are Amazon Alexa and Google Home limited to our bedrooms, or can they be used in hospitals? Do you envision a future where physicians work hand-in-hand with voice AI to revolutionize healthcare delivery? AI is the future of physician-machine interaction...

Accurately detecting crack localization is not an easy task. This book addresses important issues in detecting crack-like objects and provides a practical smart pavement surface inspection system using deep learning.

Artificial Intelligence (AI) in general and machine learning (ML) and deep learning (DL) in particular and related digital technologies are a couple of fledging paradigms that next-generation healthcare services are sprinting towards. These digital...

Smart cities with various technological innovations have played an important role and influenced society as well. Due to voluminous data transactions within smart cities, security and privacy concerns need to be dealt with. This book discusses the...

This book aims at providing theoretical knowledge in the application of swarm intelligence and evolutionary computation including several recent meta-heuristic algorithms and also providing practical emerging applications in machine learning and deep...

This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing.

This book focuses on different algorithms and models related to AI, big data, and IoT used for various domains. It enables the reader to have a broader and deep understanding of several perspectives, about the dynamics, challenges, and opportunities...

This book takes an interdisciplinary approach covering health care, cognitive computing, and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and images (X-rays, MRI, CT) are explored, analyzed, and processed.

This book presents new cyber-physical security findings for Industry 4.0 using emerging technologies like Artificial Intelligence, Data Mining and Applied Mathematics which are the essential components for processing data, recognizing patterns,...

This book discusses electroencephalogram (EEG) signal processing using effective methodology and algorithms. It provides a basic introduction on EEG, classification of different components and scope of processing EEG signal and its applications. Specific...

It will help future research be done in healthcare. It also explores the recent progress in several computing technologies and evaluates the performance based on today's betterment compared to previous development in the technology.

This book presents post-estimation and predictions strategies for the host of useful statistical models with applications in data science. Combining statistical learning and machine learning techniques in a unique and optimal way, it will help...

En el paisaje siempre cambiante de la tecnología, el Aprendizaje Automático (ML) se encuentra en la vanguardia, impulsando la innovación y remodelando la forma en que interactuamos con el mundo digital. "Descifrando el Código: Introducción al Aprendizaje...

"The Power and Potential of Natural Language Processing" is a comprehensive guide to understanding the exciting world of NLP. From the basics of text processing and language modeling to advanced techniques like neural networks and deep...

The generation of concept maps from domain text using machine learning and deep learning techniques is a promising area of research that aims to assist in the organization and comprehension of information. Concept maps are graphical representations of...

Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large...