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Reduce Friction In Your Business Analytics Through Entity Centric Data Modeling

Data Engineering Podcast

Summary For business analytics the way that you model the data in your warehouse has a lasting impact on what types of questions can be answered quickly and easily. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles.

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New Approaches For Detecting AI-Generated Profile Photos

LinkedIn Engineering

Co-authors: Shivansh Mundra , Gonzalo Aniano Porcile , Smit Marvaniya , Hany Farid A core part of what we do on the Trust Data Team at LinkedIn is create, deploy, and maintain models that detect and prevent many types of abuse. This spans the detection and prevention of fake accounts, account takeovers, and policy-violating content.

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An AI Chat Bot Wrote This Blog Post …

DataKitchen

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

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Data Engineering Weekly #167

Data Engineering Weekly

Meta: OpenEQA - From word models to world models Will AI agents soon become a common fixture in our homes and an integral part of our daily lives? link] Github: 4 ways GitHub engineers use GitHub Copilot The impact of LLM on software development is undeniable.

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What are the Commonly Used Machine Learning Algorithms?

Knowledge Hut

Machine Learning is a sub-branch of Artificial Intelligence, used for the analysis of data. It learns from the data that is input and predicts the output from the data rather than being explicitly programmed. If ML algorithms consume more amounts of data while solving a problem, it results in better performance.

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Data Engineering Weekly #157

Data Engineering Weekly

RudderStack is the Warehouse Native CDP, built to help data teams deliver value across the entire data activation lifecycle, from collection to unification and activation. Joe Reis: Definition of Data Modeling & What Data Modeling Is not Joe raised a very fundamental question in data engineering.

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How to get datasets for Machine Learning?

Knowledge Hut

Also called data storage areas , they help users to understand the essential insights about the information they represent. Datasets play a crucial role and are at the heart of all Machine Learning models. Machine learning uses algorithms that comb through data sets and continuously improve the machine learning model.