Mathematical theory of computation Books

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...

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 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...

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...

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...

AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. The AI framework comprises of bootstrapping to create multiple training and testing data sets with various characteristics,...

Are you excited about Artificial Intelligence and want to get started?Are you excited about Machine Learning and want to learn how to implement in Python?The book below is the answer.Given the large amounts of data we use everyday; whether it is in the...

Apply machine learning to streaming data with the help of practical examples, and deal with challenges that surround streamingKey Features:Work on streaming use cases that are not taught in most data science coursesGain experience with state-of-the-art...

Leverage top XAI frameworks to explain your machine learning models with ease and discover best practices and guidelines to build scalable explainable ML systemsKey Features:Explore various explainability methods for designing robust and scalable...

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes many recent supervised and unsupervised machine learning methodologies such as...

Intelligent Support for Computer Science Education presents the authors' research journey into the effectiveness of human tutoring, with the goal of developing educational technology that can be used to improve introductory Computer Science education...

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization describes such algorithms as Locally Linear Embedding (LLE), Laplacian Eigenmaps, Isomap, Semidefinite Embedding, and t-SNE to resolve the problem of dimensionality...

This book covers the state-of-the-art techniques of machine learning and their applications in the medical field. It presents several Computer-aided diagnosis (CAD) systems, which have played an important role in the diagnosis of several diseases in...

Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in...

Physical and behavioral biometric technologies such as fingerprinting, facial recognition, voice identification, etc. have enhanced the level of security substantially in recent years. Governments and corporates have employed these technologies to...

From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What's more, it presents an organizing framework that makes a convincing argument that data science is a course distinct...

R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required – this book will take you methodically through every stage of applying machine learning.Key Features:Harness the power of R...

Monte Carlo methods, in particular those based on Markov chains and on interacting particle systems, are by now tools that are routinely used in machine learning. These methods have had a profound impact on statistical inference in a wide range of...

Dimension reduction is the mapping of data to a lower dimensional space such that uninformative variance in the data is discarded, or such that a subspace in which the data lives is detected. Dimension reduction has a long history as a method for data...

Medical imaging is an indispensable tool for modern healthcare. Machine leaning plays an essential role in the medical imaging field, with applications including medical image analysis, computer-aided diagnosis, organ/lesion segmentation, image fusion,...

Optimization from Human Genes to Cutting Edge Technologies The challenges faced by industry today are so complex that they can only be solved through the help and participation of optimization ex­ perts. For example, many...

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its...

Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity:...

This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare,...

The bright future of green IoT will change our tomorrow environment to become healthier and green, with very high quality of service that is socially, environmentally, and economically sustainable. This book covers the most recent advances in IoT, it...

This book covers the fundamentals of IoT and healthcare systems for carrying out system architectures, protocols, wearable devices, and interoperability. It explores major challenges in AI and smart computing in resource-constrained IoT-based...

Smart Sensor Networks (WSNs) using AI has left a mark on the lives of all by aiding in various sectors such as manufacturing, education, healthcare, and monitoring of the environment and industries. This book covers recent AI applications and explores...

Implementing new information technologies into the healthcare sector can provide alternatives to managing patients' health records, systems, and improving the quality of care received. This book provides an overview of IoT technologies related to the...

Metaheuristic Algorithms in Industry 4.0 provides a guiding light to engineers, researchers, students, faculty and other professionals engaged in exploring and implementing industry 4.0 solutions in various systems and processes.

This book describes how newly emerging Artificial Intelligence (AI) technologies will provide unprecedented opportunities to penetrate technology and automation into everything we do, and at the same time, provide a huge playing field for businesses to...

This book provides insight into the recent advances of applications, statistical methods, and mathematical modeling for the healthcare industry.

Das vorliegende Buch ist ein praktischer Fuhrer fOr die Erstellung von Schrift­ satz und Grafik mit dem HP LaserJet. An uber 20 ausfOhrlich kommentierten Beispieldokumenten wird ein Kurs des "Desktop Publishing" absolviert, der...

Das vorliegende Buch bietet die mathematischen Grundlagen und gibt Erläuterungen zu den Gebieten der Zins-, Renten-, Tilgungs- und lnvestitionsrechnung, ferner für die Renditen von Kapitalanlagen sowie der Statistik. ...

Der vorliegende Band beschiiftigt sich mit der Gewinnung von Zahlenwerten zu elliptischen Integralen erster und zweiter Gattung. Dies geschieht hier nicht mittels Tabellen und Interpolation, sondern durch geeignete ...

Dieses Buch entstand aus Skripten, die zur Lehrveranstaltung OBERSETZERBAU im Fachbereich Infonnatik der Technischen Universitat Berlin angefertigt wurden. Die Lehrveranstaltung wird seit 1972 durchgeflihrt und wurde als ein...

The focus of this book is on the application of AI methods in the field of protection of different types and topologies of transmission and distribution lines explaining the latest pattern-recognition- based methods applied to detection, classification,...

The resurgence of artificial intelligence has been fueled by the availability of the present generation of high-performance computational tools and techniques. This book is designed to provide introductory guidance to artificial intelligence,...

This book focuses on implementation of a possible Hybrid Image Examination technique for medical images describing various image thresholding and segmentation methods along with essential details, such as test image preparation, implementation of a...

This book covers theory and practical knowledge of probabilistic data structures (PDS) and blockchain (BC) concepts. It introduces the applicability of PDS in BC and each PDS has been explained through code snippets and illustrative examples. Further, it...