Database design and theory

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.

Do you know what to do if your web application goes viral and usage suddenly explodes?

Whether youre building a social media site or an internal-use enterprise application, this hands-on guide shows you the connection between MongoDB and the business problems its designed to solve.

This book provides a comprehensive exploration of Industry 6.

El concepto de Big Data no solo hace referencia a grandes colecciones de datos, caracterizadas tanto por su volumen como por la variedad de formatos, sino que incluye también los sistemas y las tecnologías encargadas de almacenar, procesar y dar valor a toda esa información.

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.

Used by more than 80% of Fortune 100 companies, Apache Kafka has become the de facto event streaming platform.

Essential to database design, entity-relationship (ER) diagrams are known for their usefulness in data modeling and mapping out clear database designs.

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.

Metaphor and Corpus Linguistics: Building and Investigating an English as a Medium of Instruction Corpus offers a model for building a corpus of oral EMI seminars.

It is a major challenge to migrate very large databases from one system, say for example, to transfer critical data from Oracle to SQL Server.

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.

Manage your data with a system designed to support modern application development.

DataOps is a new way of delivering data and analytics that is proven to get results.

Cyberspace is changing the face of crime.

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.

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.

Discover the power of location data to build effective, intelligent data models with Geospatial ecosystemsKey FeaturesManipulate location-based data and create intelligent geospatial data modelsBuild effective location recommendation systems used by popular companies such as UberA hands-on guide to help you consume spatial data and parallelize GIS operations effectivelyBook DescriptionData scientists, who have access to vast data streams, are a bit myopic when it comes to intrinsic and extrinsic location-based data and are missing out on the intelligence it can provide to their models.

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.

Understand the Blockchain revolution and get to grips with Ethereum, Hyperledger Fabric, and Corda.

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

Many librarians' job responsibilities increasingly require them to understand and handle data.

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

Present energy systems are undergoing a radical transformation, driven by the urgent need to address the climate change crisis.

Do you know what to do if your web application goes viral and usage suddenly explodes?

JavaScript is the native language of the Internet.

Over the next few decades, machine learning and data science will transform the finance industry.

Databases have become an integral part of modern-day life.

This book is intended to serve as a bridge in statistics for graduates and business practitioners interested in using their skills in the area of data science and analytics as well as statistical analysis in general.

Discovery tools are now becoming more common in the academic library landscape, and more products are now available from vendors.

A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world.

Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key FeaturesA step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZA modern, practical and computational approach to Bayesian statistical modelingA tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises.

Everything you need to know to apply data contracts and build a truly data-driven organization that harnesses quality data to deliver tangible business valuePurchase of the print or Kindle book includes a free PDF eBookKey FeaturesUnderstand data contracts and their power to resolving the problems in contemporary data platformsLearn how to design and implement a cutting-edge data platform powered by data contractsAccess practical guidance from the pioneer of data contracts to get expert insights on effective utilizationBook DescriptionDespite the passage of time and the evolution of technology and architecture, the challenges we face in building data platforms persist.

The use of dynamic models in the development of information systems is regarded by many researchers as a promising issue in design support.

Get up and running with the fundamentals of Bitcoin and blockchainKey FeaturesLearn quick, effective, and easy ways to master blockchain and Bitcoin Understand the impact of decentralization and discover ways to tackle it Explore the future of Bitcoin and blockchain and implement them in a business networkBook DescriptionBlockchain is a distributed database that enables permanent, transparent, and secure storage of data.

This book presents advanced research on smart health technologies, focusing on the innovative transformations in diagnosis and treatment planning using medical imaging and data analysed by data science techniques.

Discover techniques to summarize the characteristics of your data using PyPlot, NumPy, SciPy, and pandasKey FeaturesUnderstand the fundamental concepts of exploratory data analysis using PythonFind missing values in your data and identify the correlation between different variablesPractice graphical exploratory analysis techniques using Matplotlib and the Seaborn Python packageBook DescriptionExploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset.

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