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Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R About This Book Predict and use a probabilistic graphical models (PGM) as an expert system Comprehend how your computer can learn Bayesian modeling to solve real-world problems Know how to prepare data and feed the models by using the appropriate algorithms from the appropriate R package Who This Book Is For This book is for anyone who has to deal with lots of data and draw conclusions from it, especially when the data is noisy or uncertain. Data scientists, machine learning enthusiasts, engineers, and those who curious about the latest advances in machine learning will find PGM interesting. What You Will Learn Understand the concepts of PGM and which type of PGM to use for which problem Tune the model's parameters and explore new models automatically Understand the basic principles of Bayesian models, from simple to advanced Transform the old linear regression model into a powerful probabilistic model Use standard industry models but with the power of PGM Understand the advanced models used throughout today's industry See how to compute posterior distribution with exact and approximate inference algorithms In Detail Probabilistic graphical models (PGM, also known as graphical models) are a marriage between probability theory and graph theory. Generally, PGMs use a graph-based representation. Two branches of graphical representations of distributions are commonly used, namely Bayesian networks and Markov networks. R has many packages to implement graphical models. We'll start by showing you how to transform a classical statistical model into a modern PGM and then look at how to do exact inference in graphical models. Proceeding, we'll introduce you to many modern R packages that will help you to perform inference on the models. We will then run a Bayesian linear regression and you'll see the advantage of going probabilistic when you want to do prediction. Next, you'll master using R packages and implementing its techniques. Finally, you'll be presented with machine learning applications that have a direct impact in many fields. Here, we'll cover clustering and the discovery of hidden information in big data, as well as two important methods, PCA and ICA, to reduce the size of big problems. Style and approach This book gives you a detailed and step-by-step explanation of each mathematical concept, which will help you build an...

R (Computer program language) --- Probabilistic databases. --- Graphical modeling (Statistics) --- Multivariate analysis --- Probabilistic database systems --- Databases --- GNU-S (Computer program language) --- Domain-specific programming languages --- Graphic methods

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Databases. --- Java (Computer program language) --- SQL server. --- Object-oriented programming languages --- JavaSpaces technology --- Data banks --- Data bases --- Databanks --- Database systems --- Computer files --- Electronic information resources --- Microsoft SQL server

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This book constitutes revised selected papers from two VLDB workshops: The International Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances, Poly 2020, and the 6th International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2020, which were held virtually on August 31 and September 4, 2020. For Poly 2020, 4 full and 3 short papers were accepted from 10 submissions; and for DMAH 2020, 7 full and 2 short papers were accepted from a total of 15 submissions. The papers were organized in topical sections as follows: Privacy, Security and/or Policy Issues for Heterogenous Data; COVID-19 Data Analytics and Visualization; Deep Learning based Biomedical Data Analytics; NLP based Learning from Unstructured Data; Biomedical Data Modelling and Prediction.

Application software. --- Database management. --- Machine learning. --- Computer Applications. --- Database Management. --- Machine Learning. --- Learning, Machine --- Artificial intelligence --- Machine theory --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Electronic data processing --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Medical informatics --- Database management --- Federated database systems --- Database systems, Federated --- FDBSs (Federated database systems) --- Federated systems (Database management) --- Systems, Federated (Database management) --- Metadatabases --- Management

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What is this Report about? Inventions can be patented, knowledge can be protected through the law of trade secrets, but information itself? The form or medium of information can be protected by copyright but information itself is more difficult. It cannot be owned. So how can the law effectively protect it? Both the law - and hence the commercial realities - remain uncertain. Professional advisers must at least be fully up to speed with what the law currently says [and doesn't say] and what the implications are. This timely new Special Report examines the current EU [and so EEA] law on the

Databases. --- Databases --- Copyright --- Literary property --- Property, Literary --- Intangible property --- Intellectual property --- Anti-copyright movement --- Authors and publishers --- Book registration, National --- Patent laws and legislation --- Data banks --- Data bases --- Databanks --- Database systems --- Computer files --- Electronic information resources --- Law and legislation

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Develop real-time practical DApps using Ethereum and JavaScript About This Book Create powerful, end-to-end applications for Blockchain using Ethereum Write your first program using the Solidity programming language Change the way you think and design your applications by using the all new database-Blockchain Who This Book Is For This book is for JavaScript developers who now want to create tamper-proof data (and transaction) applications using Blockchain and Ethereum. Those who are interested in cryptocurrencies and the logic and database empowering it will find this book extremely useful. What You Will Learn Walk through the basics of the Blockchain technology Implement Blockchain's technology and its features, and see what can be achieved using them Build DApps using Solidity and Web3.js Understand the geth command and cryptography Create Ethereum wallets Explore consortium blockchain In Detail Blockchain is a decentralized ledger that maintains a continuously growing list of data records that are secured from tampering and revision. Every user is allowed to connect to the network, send new transactions to it, verify transactions, and create new blocks, making it permission-less. This book will teach you what Blockchain is, how it maintains data integrity, and how to create real-world Blockchain projects using Ethereum. With interesting real-world projects, you will learn how to write smart contracts which run exactly as programmed without any chance of fraud, censorship, or third-party interference, and build end-to-end applications for Blockchain. You will learn about concepts such as cryptography in cryptocurrencies, ether security, mining , smart contracts, solidity, and more. You will also learn about web sockets, various API services for Ethereum, and much more. The blockchain is the main technical innovation of bitcoin, where it serves as the public ledger for bitcoin transactions. Style and approach This is a project-based guide that not only gets you up and running with Blockchain, but also lets you create intuitive real-world applications that will make you an independent Blockchain developer. Downloading the example code for this book. You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the code file.

Distributed databases. --- Distributed data bases --- Distributed database systems --- Databases --- Cyberinfrastructure --- Ethereum (Distributed computing platform) --- Blockchains (Databases). --- COMPUTERS --- Electronic data processing --- JavaScript (Computer program language). --- Data Processing. --- General. --- Electronic Commerce. --- Distributed processing. --- Ethereum (Distributed computing platform).