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Incremental Machine Learning for Linked Data Event Streams

Towards AI

Unlocking the Power of Real-time Predictions: An Introduction to Incremental Machine Learning for Linked Data Event Streams Photo by Isaac Smith on Unsplash This article discusses online machine learning, one of the most exciting subdomains of machine learning theory. LDES workbench in Apache NIFI (Image by the author.)

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Linked Data Event Streams and TimescaleDB for Real-time Timeseries Data Management

Towards AI

How to consume a Linked Data Event Stream and store it in a TimescaleDB database Photo by Scott Graham on Unsplash Linked data event stream Linked Data Event Streams represent and share fast and slow-moving data on the Web using the Resource Description Framework (RDF). and PostgreSQL 14.4

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Web 3.0- Privacy, Ethics and Other Moral Aspects

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. links data or objects with highly organized semantic relationships instead of linking information or publications for people and computers to read […]. The post Web 3.0- Privacy, Ethics and Other Moral Aspects appeared first on Analytics Vidhya.

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Importance of Data Governance and its Principles

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Source: [link] What is DATA by Definition? Source: [link] Data are details, facts, statistics, or pieces of information, typically numerical. Data are a set of values of qualitative or quantitative variables about one or more persons or objects.

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Building cars in a changing world: Audi’s Integrated Approach with IBM Planning Analytics

IBM Journey to AI blog

It was equally important that this infrastructure contained consistent metadata and data structures across all entities, preventing data redundancy and streamlining processes. The primary goal in adopting a planning and analytics solution was to link data and processes across departments.

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Saldor: The Web Scraper for AI

Marktechpost

Using data extraction, Saldor locates and retrieves the required data from the target websites. This can contain different information, text, pictures, and links. Data Cleaning: To guarantee the quality and consistency of the extracted data, it is cleaned and formatted.

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This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines

Marktechpost

Modeling the underlying academic data as an RDF knowledge graph (KG) is one efficient method. This makes standardization, visualization, and interlinking with Linked Data resources easier. As a result, scholarly KGs are essential for converting document-centric academic material into linked and automatable knowledge structures.