Information architecture

This volume presents four machine-independent theories of computational complexity, which have been chosen for their intrinsic importance and practical relevance.

This book describes systematic methods for winning in differential games of pursuit and evasion and illustrates the scope and application of the developed procedures.

A comprehensive guide to mastering the most advanced Hadoop 3 conceptsKey FeaturesGet to grips with the newly introduced features and capabilities of Hadoop 3Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystemSharpen your Hadoop skills with real-world case studies and codeBook DescriptionApache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data.

Develop modern solutions with Snowflake's unique architecture and integration capabilities; process bulk and real-time data into a data lake; and leverage time travel, cloning, and data-sharing features to optimize data operationsKey FeaturesBuild and scale modern data solutions using the all-in-one Snowflake platformPerform advanced cloud analytics for implementing big data and data science solutionsMake quicker and better-informed business decisions by uncovering key insights from your dataBook DescriptionSnowflake is a unique cloud-based data warehousing platform built from scratch to perform data management on the cloud.

Just as a traveler crossing a continent won't sense the curvature of the earth, one lifetime of reading can't grasp the largest patterns organizing literary history.

Gain practical insights by exploiting data in your business to build advanced predictive modeling applications Key Features A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Learn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Master open source Python tools to build sophisticated predictive models Book Description Social Media and the Internet of Things have resulted in an avalanche of data.

Network Flow, Transportation, and Scheduling; Theory and Algorithms

Graphs, Dynamic Programming and Finite Games

Information systems are part and parcel of organizations.

Get up and running with Oracle's premium cloud blockchain services and build distributed blockchain apps with easeKey FeaturesDiscover Hyperledger Fabric and its components, features, qualifiers, and architectureGet familiar with the Oracle Blockchain Platform and its unique featuresBuild Hyperledger Fabric-based business networks with Oracle's premium blockchain cloud serviceBook DescriptionHyperledger Fabric empowers enterprises to scale out in an unprecedented way, allowing organizations to build and manage blockchain business networks.

Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering how you can use deep learning models in your software applications with Microsoft Cognitive ToolkitKey FeaturesUnderstand the fundamentals of Microsoft Cognitive Toolkit and set up the development environment Train different types of neural networks using Cognitive Toolkit and deploy it to productionEvaluate the performance of your models and improve your deep learning skillsBook DescriptionCognitive Toolkit is a very popular and recently open sourced deep learning toolkit by Microsoft.

If you want to master the art and science of reverse engineering code with IDA Pro for security R&D or software debugging, this is the book for you.

Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natural language processing.

Studies in Logic publishes monographs and occasionally edited volumes in the area of mathematical logic and its applications.

Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystemKey FeaturesGet to grips with building faster and more robust deep learning architecturesInvestigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorchApply deep neural networks (DNNs) to computer vision problems, NLP, and GANsBook DescriptionIn order to build robust deep learning systems, you'll need to understand everything from how neural networks work to training CNN models.

Logic in Algebraic Form

Study data analysis and visualization to successfully analyze data with RKey FeaturesGet to grips with data cleaning methodsExplore statistical concepts and programming in R, including best practicesBuild a data science project with real-world examplesBook DescriptionR Programming Fundamentals, focused on R and the R ecosystem, introduces you to the tools for working with data.

Big data processing and analytics at speed and scale using command line tools.

Integral Equations and Stability of Feedback Systems

Supervised and unsupervised machine learning made easy in Scala with this quick-start guide.

Adaptive, Learning, and Pattern Recognition Systems; theory and applications

The ambition of this volume is twofold: to provide a comprehensive overview of the field and to serve as an indispensable reference work for anyone who wants to work in it.

To deliver the insights that give them a competitive advantage, organizations increasingly turn to the proven Medallion architecture.

The Theory of Semisets

Process Algebra is a formal description technique for complex computer systems, especially those involving communicating, concurrently executing components.

The second part of this Handbook presents a choice of material on the theory of automata and rewriting systems, the foundations of modern programming languages, logics for program specification and verification, and some chapters on the theoretic modelling of advanced information processing.

Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystemKey FeaturesGet to grips with building faster and more robust deep learning architecturesInvestigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorchApply deep neural networks (DNNs) to computer vision problems, NLP, and GANsBook DescriptionIn order to build robust deep learning systems, you'll need to understand everything from how neural networks work to training CNN models.

Introduction to Operations Research

Quantum Detection and Estimation Theory

Formal Systems and Recursive Functions

Perform Interactive Data Analysis with Smarter Visualizations and Support your Enterprise-wide Analytical Needs Key Features Get a practical demonstration of discovering data for sales, human resources, and more using Qlik Sense Create dynamic dashboards for business intelligence and predictive analytics Create and collaborate comprehensive analytical solutions using Rattle and Qlik Sense Book Description Qlik Sense is powerful and creative visual analytics software that allows users to discover data, explore it, and dig out meaningful insights in order to make a profit and make decisions for your business.

Holding On to Reality is a brilliant history of information, from its inception in the natural world to its role in the transformation of culture to the current Internet mania and is attendant assets and liabilities.

Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learningKey FeaturesGet up and running with graph analytics with the help of real-world examplesExplore various use cases such as fraud detection, graph-based search, and recommendation systemsGet to grips with the Graph Data Science library with the help of examples, and use Neo4j in the cloud for effective application scalingBook DescriptionNeo4j is a graph database that includes plugins to run complex graph algorithms.

Handbook of Probabilistic Models carefully examines the application of advanced probabilistic models in conventional engineering fields.

Model Theory For Infinitary Logic

Learn through hands-on exercises covering a variety of topics including data connections, analytics, and dashboards to effectively prepare for the Tableau Desktop Certified Associate examKey FeaturesPrepare for the Tableau Desktop Certified Associate exam with the help of tips and techniques shared by expertsImplement Tableau's advanced analytical capabilities such as forecastingDelve into advanced Tableau features and explore best practices for building dashboardsBook DescriptionThe Tableau Desktop Certified Associate exam measures your knowledge of Tableau Desktop and your ability to work with data and data visualization techniques.

Optimization of Stochastic Systems is an outgrowth of class notes of a graduate level seminar on optimization of stochastic systems.

Fractional Calculus: Bridging Theory with Computational and Contemporary Advances is an authoritative and comprehensive guide that delves into the world of fractional calculus, offering a unique blend of theoretical foundations, numerical algorithms, practical applications, and innovative perspectives.

Enhance your simulation modeling skills by creating and analyzing digital prototypes of a physical model using Python programming with this comprehensive guideKey FeaturesLearn to create a digital prototype of a real model using hands-on examplesEvaluate the performance and output of your prototype using simulation modeling techniquesUnderstand various statistical and physical simulations to improve systems using PythonBook DescriptionSimulation modeling helps you to create digital prototypes of physical models to analyze how they work and predict their performance in the real world.

Understand how machine learning works and get hands-on experience of using R to build algorithms that can solve various real-world problemsKey FeaturesGain a comprehensive overview of different machine learning techniquesExplore various methods for selecting a particular algorithmImplement a machine learning project from problem definition through to the final modelBook DescriptionWith huge amounts of data being generated every moment, businesses need applications that apply complex mathematical calculations to data repeatedly and at speed.

Disability interactions (DIX) is a new approach to combining cross-disciplinary methods and theories from Human Computer Interaction (HCI), disability studies, assistive technology, and social development to co-create new technologies, experiences, and ways of working with disabled people.

Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organizationKey FeaturesLearn the basics of data science and explore its possibilities and limitationsManage data science projects and assemble teams effectively even in the most challenging situationsUnderstand management principles and approaches for data science projects to streamline the innovation processBook DescriptionData science and machine learning can transform any organization and unlock new opportunities.

Extract accurate information from data to train and improve machine learning models using NumPy, SciPy, pandas, and scikit-learn librariesKey FeaturesDiscover solutions for feature generation, feature extraction, and feature selectionUncover the end-to-end feature engineering process across continuous, discrete, and unstructured datasetsImplement modern feature extraction techniques using Python's pandas, scikit-learn, SciPy and NumPy librariesBook DescriptionFeature engineering is invaluable for developing and enriching your machine learning models.

Approximate Methods in Engineering Design

Machine learning is an intimidating subject until you know the fundamentals.