Information architecture

A comprehensive end-to-end guide that gives hands-on practice in big data and Artificial IntelligenceKey FeaturesLearn to build and run a big data application with sample codeExplore examples to implement activities that a big data architect performsUse Machine Learning and AI for structured and unstructured dataBook DescriptionThe big data architects are the "e;masters"e; of data, and hold high value in today's market.

Supercharge your skills for developing powerful deep learning models and distributing them at scale efficiently using cloud servicesKey FeaturesUnderstand how to execute a deep learning project effectively using various tools availableLearn how to develop PyTorch and TensorFlow models at scale using Amazon Web ServicesExplore effective solutions to various difficulties that arise from model deploymentBook DescriptionMachine learning engineers, deep learning specialists, and data engineers encounter various problems when moving deep learning models to a production environment.

Solve all big data problems by learning how to create efficient data modelsKey FeaturesCreate effective models that get the most out of big dataApply your knowledge to datasets from Twitter and weather data to learn big dataTackle different data modeling challenges with expert techniques presented in this bookBook DescriptionModeling and managing data is a central focus of all big data projects.

Get more from your data by creating practical machine learning systems with PythonKey FeaturesDevelop your own Python-based machine learning systemDiscover how Python offers multiple algorithms for modern machine learning systemsExplore key Python machine learning libraries to implement in your projectsBook DescriptionMachine learning allows systems to learn things without being explicitly programmed to do so.

Leverage the power of machine learning on mobiles and build intelligent mobile applications with easeKey FeaturesBuild smart mobile applications for Android and iOS devicesUse popular machine learning toolkits such as Core ML and TensorFlow LiteExplore cloud services for machine learning that can be used in mobile appsBook DescriptionMachine learning presents an entirely unique opportunity in software development.

Implement decentralized blockchain applications to build scalable DappsKey FeaturesUnderstand the blockchain ecosystem and its terminologiesImplement smart contracts, wallets, and consensus protocolsDesign and develop decentralized applications using Bitcoin, Ethereum, and HyperledgerBook DescriptionThe Blockchain is a revolution promising a new world without middlemen.

Leverage the power of Java and its associated machine learning libraries to build powerful predictive modelsKey FeaturesSolve predictive modeling problems using the most popular machine learning Java libraries Explore data processing, machine learning, and NLP concepts using JavaML, WEKA, MALLET librariesPractical examples, tips, and tricks to help you understand applied machine learning in JavaBook DescriptionAs the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations.

Leverage Elastic Stack's machine learning features to gain valuable insight from your dataKey FeaturesCombine machine learning with the analytic capabilities of Elastic StackAnalyze large volumes of search data and gain actionable insight from themUse external analytical tools with your Elastic Stack to improve its performanceBook DescriptionMachine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting.

Optimize your marketing strategies through analytics and machine learningKey FeaturesUnderstand how data science drives successful marketing campaignsUse machine learning for better customer engagement, retention, and product recommendationsExtract insights from your data to optimize marketing strategies and increase profitabilityBook DescriptionRegardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry.

Learn to effectively manage data and execute data science projects from start to finish using PythonKey FeaturesUnderstand and utilize data science tools in Python, such as specialized machine learning algorithms and statistical modelingBuild a strong data science foundation with the best data science tools available in PythonAdd value to yourself, your organization, and society by extracting actionable insights from raw dataBook DescriptionPractical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science.

Leverage the power of Tableau 2019.

Process large volumes of data in real-time while building high performance and robust data stream processing pipeline using the latest Apache Kafka 2.

This book adopts a holistic interpretation of information architecture, to offer libraries and information professionals a variety of methods, tools, and techniques that may be used when designing websites and information systems that support workflows and what people require when "e;managing information"e;.

This new and updated second edition of a classic text provides a thought provoking introduction to metadata for all library and information students and professionals.

This book shows you how to harness the power of linked data and web-scale discovery systems to manage and link widely varied content across your library collection.

This highly practical handbook teaches you how to unlock the value of your existing metadata through cleaning, reconciliation, enrichment and linking and how to streamline the process of new metadata creation.

This authoritative and practical introduction to solution architecture is suitable for new entrants to the field but also of benefit to experienced professionals wishing to consolidate their knowledge and skills.

This authoritative and practical introduction to solution architecture is suitable for new entrants to the field but also of benefit to experienced professionals wishing to consolidate their knowledge and skills.

In the realm of computational intelligence, the age-old adage, "e;not everything is black and white,"e; has never been more pertinent.

Graph Databases in Action introduces you to graph database concepts by comparing them with relational database constructs.

This is the first of two books concerned with engineering design principles for Human-Computer Interaction-Engineering Design Principles (HCI-EDPs).

This is the second of two books by the authors about engineering design principles for human-computer interaction (HCI-EDPs).

This book introduces Participatory Design to researchers and students in Human-Computer Interaction (HCI).

Information systems are part and parcel of organizations.

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.

An era of big data demands datacenters, which house the computing infrastructure that translates raw data into valuable information.

Learn state-of-the-art skills to build compelling, useful, and fun Web GIS apps easily, with no programming experience required.

The Esri Guide to GIS Analysis, Volume 3: Modeling Suitability, Movement, and Interaction describes practical applications of modeling concepts in a geographic information system (GIS).

Would you like to gather big datasets, analyze them, and visualize the results, all in one program?

Would you like to gather big datasets, analyze them, and visualize the results, all in one program?