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Unbundling the Graph in GraphRAG

O'Reilly on Data

The haphazard results may be entertaining, although not quite based in fact. A Latent Space Theory for Emergent Abilities in Large Language Models ” by Hui Jiang presents a statistical explanation for emergent LLM abilities, exploring a relationship between ambiguity in a language versus the scale of models and their training data. “

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Netflix Case Study (EDA): Unveiling Data-Driven Strategies for Streaming

Analytics Vidhya

As one of the leading streaming platforms globally, Netflix has revolutionized how we consume entertainment. Introduction Welcome to our comprehensive data analysis blog that delves deep into the world of Netflix. With its vast library of movies and TV shows, it offers an abundance of choices for viewers around the world.

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Why Nonprofits Shouldn’t Use Statistics

Depict Data Studio

— Thank you to Ann Emery, Depict Data Studio, and her Simple Spreadsheets class for inviting us to talk to them about the use of statistics in nonprofit program evaluation! But then we realized that much of the time, statistics just don’t have much of a role in nonprofit work. Why Nonprofits Shouldn’t Use Statistics.

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What to expect from AI in the enterprise in 2025

CIO Business Intelligence

In 1987, Nobel prize winning economist Robert Solow famously quipped, You can see the computer age everywhere but in the productivity statistics. These will be across a number of sectors including marketing, publishing, entertainment, and education in both B2C and B2B environments. a month for a subscription service.

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Top 14 Must-Read Data Science Books You Need On Your Desk

datapine

Based on 50 real-life business intelligence examples and case studies, this book is wonderfully crafted, incredibly entertaining, insightful, enlightening, intriguing, and result-driven. One of Bernard Marr’s best offerings to date, this truly is one of the best books for data science in existence today – a must-read in today’s world.

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Top 10 AI graduate degree programs

CIO Business Intelligence

The Machine Learning Department at Carnegie Mellon University was founded in 2006 and grew out of the Center for Automated Learning and Discovery (CALD), itself created in 1997 as an interdisciplinary group of researchers with interests in statistics and machine learning. University of Texas–Austin.

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Social services provider uses artificial intelligence to provide genuine help

CIO Business Intelligence

In addition, the incapacity to properly utilize advanced analytics, artificial intelligence (AI), and machine learning (ML) shut out users hoping for statistical analysis, visualization, and general data-science features. As a result, data teams exhausted valuable time resolving problems and fixing glitches, and the approximately 1.5