Information architecture

In this book we describe the basic elements of present computational technologies that use the algorithmic languages C/C++.

Harness the power of Microsoft Fabric to develop data analytics solutions for various use cases guided by step-by-step instructionsKey FeaturesExplore Microsoft Fabric and its features through real-world examplesBuild data analytics solutions for lakehouses, data warehouses, real-time analytics, and data scienceMonitor, manage, and administer your Fabric platform and analytics system to ensure flexibility, performance, security, and controlPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionDiscover the capabilities of Microsoft Fabric, the premier unified solution designed for the AI era, seamlessly combining data integration, OneLake, transformation, visualization, universal security, and a unified business model.

Introduction to the Theory and Application of Differential Equations with Deviating Arguments 2nd edition is a revised and substantially expanded edition of the well-known book of L.

Differential and integral inequalities; theory and applications PART B: Functional, partial, abstract, and complex differential equations

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.

Build efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing frameworkKey FeaturesMaster the art of real-time big data processing and machine learning Explore a wide range of use-cases to analyze large data Discover ways to optimize your work by using many features of Spark 2.

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.

Implement real-world machine learning in a microservices architecture as well as design, build, and deploy intelligent microservices systems using examples and case studiesPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesDesign, build, and run microservices systems that utilize the full potential of machine learningDiscover the latest models and techniques for combining microservices and machine learning to create scalable systemsImplement machine learning in microservices architecture using open source applications with pros and consBook DescriptionWith the rising need for agile development and very short time-to-market system deployments, incorporating machine learning algorithms into decoupled fine-grained microservices systems provides the perfect technology mix for modern systems.

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.

Individual-based models are an exciting and widely used new tool for ecology.

How two pioneers of math and technology ushered in the computer revolutionBoolean algebra, also called Boolean logic, is at the heart of the electronic circuitry in everything we use-from our computers and cars, to home appliances.

Nonlinear Partial Differential Equations in Engineering

Optimal control theory of distributed parameter systems has been a very active field in recent years; however, very few books have been devoted to the studiy of computational algorithms for solving optimal control problems.

Get up and running with building data pipelines and creating interactive dashboards to visualize, monitor, and present a wide variety of time-series data with this comprehensive introductory guideKey FeaturesInstall, set up, and configure Grafana for real-time data analysis, visualization, and alertingVisualize and monitor data using data sources such as InfluxDB, Telegraf, Prometheus, and ElasticsearchExplore Grafana's cloud support with Microsoft Azure, Amazon CloudWatch, and Google Cloud MonitoringPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionGet ready to unlock the full potential of the open-source Grafana observability platform, ideal for analyzing and monitoring time-series data with this updated second edition.

This book provides readers with the skills they need to write computer codes that simulate convection, internal gravity waves, and magnetic field generation in the interiors and atmospheres of rotating planets and stars.

Build attractive, insightful, and powerful visualizations to gain quality insights from your dataKey FeaturesMaster Matplotlib for data visualizationCustomize basic plots to make and deploy figures in cloud environmentsExplore recipes to design various data visualizations from simple bar charts to advanced 3D plotsBook DescriptionMatplotlib provides a large library of customizable plots, along with a comprehensive set of backends.

Sentences Undecidable in Formalized Arithmetic

Applied Analysis of Composite Media: Analytical and Computational Approaches presents formulas and techniques that can used to study 2D and 3D problems in composites and random porous media.

Build a solid foundation in algorithmic trading by developing, testing and executing powerful trading strategies with real market data using PythonKey FeaturesBuild a strong foundation in algorithmic trading by becoming well-versed with the basics of financial marketsDemystify jargon related to understanding and placing multiple types of trading ordersDevise trading strategies and increase your odds of making a profit without human interventionBook DescriptionIf you want to find out how you can build a solid foundation in algorithmic trading using Python, this cookbook is here to help.

A quick start guide to visualize your Elasticsearch dataKey FeaturesYour hands-on guide to visualizing the Elasticsearch data as well as navigating the Elastic stackWork with different Kibana plugins and create effective machine learning jobs using KibanaBuild effective dashboards and reports without any hassleBook DescriptionThe Elastic Stack is growing rapidly and, day by day, additional tools are being added to make it more effective.

Transversal Theory

With the surge in big data and AI, organizations can rapidly create data products.

Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions.

Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable Spark jobsKey FeaturesWork with large amounts of agile data using distributed datasets and in-memory cachingSource data from all popular data hosting platforms, such as HDFS, Hive, JSON, and S3Employ the easy-to-use PySpark API to deploy big data Analytics for productionBook DescriptionApache Spark is an open source parallel-processing framework that has been around for quite some time now.

Step-by-step guide to build high performing predictive applications Key FeaturesUse the Python data analytics ecosystem to implement end-to-end predictive analytics projectsExplore advanced predictive modeling algorithms with an emphasis on theory with intuitive explanationsLearn to deploy a predictive model's results as an interactive applicationBook DescriptionPredictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions.

What people are saying about Search Patterns"e;Search Patterns is a delight to read -- very thoughtful and thought provoking.

Learn how to make the right decisions for your business with the help of Python recipes and the expertise of data leadersKey FeaturesLearn and practice various clustering techniques to gather market insights Explore real-life use cases from the business world to contextualize your learningWork your way through practical recipes that will reinforce what you have learnedBook DescriptionOne of the most valuable contributions of data science is toward helping businesses make the right decisions.

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.

An expert guide to implementing fast, secure, and scalable decentralized applications that work with thousands of users in real timeKey FeaturesImplement advanced features of the Ethereum network to build powerful decentralized applicationsBuild smart contracts on different domains using the programming techniques of Solidity and VyperExplore the architecture of Ethereum network to understand advanced use cases of blockchain development Book DescriptionEthereum is one of the commonly used platforms for building blockchain applications.

If youre like most R users, you have deep knowledge and love for statistics.

Mine Ether, deploy smart contracts, tokens, and ICOs, and manage security vulnerabilities of EthereumKey FeaturesBuild end-to-end decentralized Ethereum apps using Truffle, Web3, and SolidityExplore various solution-based recipes to build smart contracts and foolproof decentralized applicationsDevelop decentralized marketplaces from scratch, build wallets, and manage transactionsBook DescriptionEthereum and Blockchain will change the way software is built for business transactions.

Computer Programming and Formal Systems

Provability, Computability and Reflection

It is common wisdom that the U.

Provability, Computability and Reflection

This is the Second Edition of the highly successful introduction to the use of generating functions and series in combinatorial mathematics.

Take your first steps to becoming a fully qualified data analyst by learning how to explore complex datasetsKey FeaturesMaster each concept through practical exercises and activitiesDiscover various statistical techniques to analyze your dataImplement everything you've learned on a real-world case study to uncover valuable insightsBook DescriptionEvery day, businesses operate around the clock, and a huge amount of data is generated at a rapid pace.

The Vector-Valued Maximin

Linear Systems of Ordinary Differential Equations, with Periodic and Quasi-Periodic Coefficients

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.

As legacy and other critical systems continue to migrate online, the need for continuous operation is imperative.

Discrete Numerical Methods in Physics and Engineering

Master a range of machine learning domains with real-world projects using TensorFlow for R, H2O, MXNet, and moreKey FeaturesMaster machine learning, deep learning, and predictive modeling concepts in R 3.

A practical guide for solving complex data processing challenges by applying the best optimizations techniques in Apache Spark.

Get up and running with machine learning life cycle management and implement MLOps in your organizationKey FeaturesBecome well-versed with MLOps techniques to monitor the quality of machine learning models in productionExplore a monitoring framework for ML models in production and learn about end-to-end traceability for deployed modelsPerform CI/CD to automate new implementations in ML pipelinesBook DescriptionEngineering MLps presents comprehensive insights into MLOps coupled with real-world examples in Azure to help you to write programs, train robust and scalable ML models, and build ML pipelines to train and deploy models securely in production.

Create and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with JupyterKey FeaturesLearn how to use Jupyter 5.

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.

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.

Get up and running with machine learning life cycle management and implement MLOps in your organizationKey FeaturesBecome well-versed with MLOps techniques to monitor the quality of machine learning models in productionExplore a monitoring framework for ML models in production and learn about end-to-end traceability for deployed modelsPerform CI/CD to automate new implementations in ML pipelinesBook DescriptionEngineering MLps presents comprehensive insights into MLOps coupled with real-world examples in Azure to help you to write programs, train robust and scalable ML models, and build ML pipelines to train and deploy models securely in production.