Machine learning Books

This book provides a holistic overview of all aspects of federated AI, which allows creation of real-world applications in contexts where data is dispersed in many different locations.

Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies.  It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent...

Artificial Intelligence Techniques in IoT Sensor Networks is a technical book which can be read by researchers, academicians, students and professionals interested in artificial intelligence (AI), sensor networks and Internet of Things (IoT). This book...

This book presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining...

Machine Learning and Models for Optimization in Cloud's main aim is to meet the user requirement with high quality of service, least time for computation and high reliability. With increase in services migrating over cloud providers, the load over the...

One of the major concerns of theoretical computer science is the classifi­ cation of problems in terms of how hard they are. The natural measure of difficulty of a function is the amount of time needed to compute it (as a...

Artificial intelligence (AI) and machine learning (ML) techniques play an important role in our daily lives by enhancing predictions and decision-making for the public in several fields such as financial services, real estate business, consumer goods,...

Artificial intelligence (AI) stands out as a transformational technology of the digital age. Its practical applications are growing very rapidly. One of the chief reasons AI applications are attaining prominence, is in its design to learn continuously,...

The book familiarizes readers with fundamental concepts and issues related to computer vision and major approaches that address them. The focus of the book is on image acquisition and image formation models, radiometric models of image formation, image...

Get well versed with state-of-the-art techniques to tailor training processes and boost the performance of computer vision models using machine learning and deep learning techniquesKey Features:Develop, train, and use deep learning algorithms for...

Implement various state-of-the-art architectures, such as GANs and autoencoders, for image generation using TensorFlow 2.x from scratchKey FeaturesUnderstand the different architectures for image generation, including autoencoders and GANsBuild models...

Work through over 50 recipes to develop smart applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico using the power of machine learningKey FeaturesTrain and deploy ML models on Arduino Nano 33 BLE Sense and Raspberry Pi PicoWork with different...

Publisher's Note: This edition from 2018 is outdated and is not compatible with TensorFlow 2 or any of the most recent updates to Python libraries. A new second edition, updated for 2020 with coverage of neural network implementation, reinforcement...

Online auctions are one of the most fundamental facets of the modern economy and power an industry generating hundreds of billions of dollars a year in revenue. Online auction theory has historically focused on the question of designing the best way to...

Multi-armed bandits is a rich, multi-disciplinary area that has been studied since 1933, with a surge of activity in the past 10-15 years. This is the first monograph to provide a textbook like treatment of the subject.The work on multi-armed bandits can...

This book focuses on the basic concepts and the related technologies of data mining for social medial. Topics include: big data and social data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media...

Expert Bytes: Computer Expertise in Forensic Documents - Players, Needs, Resources and Pitfalls -introduces computer scientists and forensic document examiners to the computer expertise of forensic documents and assists them with the design of...

Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social...

A significant amount of effort in neural modeling is directed towards understanding the representation of information in various parts of the brain, such as cortical maps [6], and the paths along which sensory information is processed. Though the time...

Parallel Numerical Computations with Applications contains selected edited papers presented at the 1998 Frontiers of Parallel Numerical Computations and Applications Workshop, along with invited papers from leading...

1 Invariants of Behavior: Constancy and Variability in Neural Systems andBehavior SummaryAcknowledgementsForewordPart I Invariants of Behavior2 Introduction3 Invariances in Theory4 Empirical Assessmentsof Invariance5 Modeling and Invariance6 Dynamical...

Random Generation of Trees is about a field on the crossroads between computer science, combinatorics and probability theory. Computer scientists need random generators for performance analysis, simulation, image synthesis,...

Models.- Changing Challenges for Collaborative Algorithmics.- Arm++: A Hybrid Association Rule Mining Algorithm.- Multiset Rule-Based Programming Paradigm for Soft-Computing in Complex Systems.- Evolutionary Paradigms.- Artificial Neural Networks.- Swarm...

Physics of Data Science and Machine Learning links fundamental concepts of physics to data science, machine learning, and artificial intelligence for physicists looking to integrate these techniques into their work.This book is written explicitly for...

The Role of Study Habits in Academic SuccessAs students, we often find ourselves overwhelmed with the demands of academic life. From juggling multiple assignments to preparing for exams, it can be challenging to stay on top of our studies. However, one...

In the realm of education, one size does not fit all. Every student is unique, with their own abilities, strengths, and challenges. Hence, it is imperative for educators and curriculum developers to embrace individualized learning to ensure that every...

What is Demand Forecasting?Demand forecasting is a critical aspect of operations and supply chain management that helps businesses predict the future demand for their products or services. It involves using historical data, statistical models, and market...

Natural Language Processing (NLP) is a rapidly evolving field that has gained significant attention in recent years. It has revolutionized the way we interact with machines and has become an integral part of many applications we use daily, such as...

Machine learning has become a buzzword in today's technological landscape, and it is crucial for everyone, regardless of their background, to have a basic understanding of this concept. This subchapter aims to demystify machine learning and provide a...

Explore the cosmic secrets of Distributed Processing for Deep Learning applications. KEY FEATURES  ●In-depth practical demonstration of ML/DL concepts using Distributed Framework.● Covers graphical illustrations and visual explanations for...

DESCRIPTION "High-Performance Algorithmic Trading using AI" is a comprehensive guide designed to empower both beginners and experienced professionals in the finance industry. This book equips you with the knowledge and tools to build sophisticated,...

This book describes advanced flows and methodologies for the design and implementation of system-on-chip (SoC).

Create and improve high-quality automated forecasts for time series data that have strong seasonal effects, holidays, and additional regressors using PythonKey FeaturesLearn how to use the open-source forecasting tool Facebook Prophet to improve your...

A comprehensive guide for data scientists to master effective data cleaning tools and techniquesKey Features:Think about your data intelligently and ask the right questionsMaster data cleaning techniques using hands-on examples belonging to diverse...

In recent years, IT application scenarios have evolved in very innovative ways. Highly distributed networks have now become a common platform for large-scale distributed programming, high bandwidth communications are...

This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI...

The next big area within the information and communication technology field is Artificial Intelligence (AI). The industry is moving to automate networks, cloud-based systems (e.g., Salesforce), databases (e.g., Oracle), AWS machine learning (e.g., Amazon...

This investigation explores the thrilling potential of brain waves for a new generation identification system. The study aims to harness the unique characteristics of brain waves as a novel and secure method for individual identification.Researchers...

This book is about quantum computing and quantum algorithms. The book starts with a chapter introducing the basic rules of quantum mechanics and how they can be used to build quantum circuits and perform computations.Further, Grover's algorithm is...

Discover how to build decision trees using SAS Viya!Tree-Based Machine Learning Methods in SAS Viya covers everything from using a single tree to more advanced bagging and boosting ensemble methods. The book includes discussions of tree-structured...

Take tiny steps to enter the big world of data science through this interesting guideKey Features:Learn the fundamentals of machine learning and build your own intelligent applicationsMaster the art of building your own machine learning systems with this...

In this monograph, the authors present an introduction to the framework of variational autoencoders (VAEs) that provides a principled method for jointly learning deep latent-variable models and corresponding inference models using stochastic gradient...

The Enigma code machine was used extensively by German armed forces in WWII. To counter its use, the British developed a massive codebreaking project which successfully captured and decoded huge numbers of German messages. This effort was so secret that...

Financial Machine Learning surveys the nascent literature on machine learning in the study of financial markets. The authors highlight the best examples of what this line of research has to offer and recommend promising directions for future research...

Call-by-push-value is a programming language paradigm that, surprisingly, breaks down the call-by-value and call-by-name paradigms into simple primitives. This monograph, written for graduate students and researchers, exposes...

Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML). ML, as the driving force of the...