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Solving Autocorrelation Problems in General Linear Model on a Real-World Application | by Rodrigo da Motta | Dec, 2023

Delving into one of the most common nightmares for data scientists Introduction One of the biggest problems in linear regression is autocorrelated residuals. In this context, this article revisits linear regression, delves into the Cochrane–Orcutt procedure as a way to solve this problem, and explores a real-world application in fMRI brain activation analysis. Photo by…

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Top 10 Accounting Problems & Solutions in 2024

Accounting problems have never been an easy issue to solve, but today presents some unique challenges. The IRS is ramping up its compliance and audit efforts while cross-border trade and transactions increase complexity for firms of all sizes. Although the Financial Accounting Standards Board (FASB) claims to be trying to keep GAAP accounting requirements nimble…

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Evolution in ETL: How Skipping Transformation Enhances Data Management

Image by Editor   Few data concepts are more polarizing than ETL (extract-transform-load), the preparation technique that has dominated enterprise operations for several decades. Developed in the 1970s, ETL shined during an era of large-scale data warehouses and repositories. Enterprise data teams centralized data, layered reporting systems and data science models on top, and…

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This AI Paper Unveils HyperDreamer: An Advancement in 3D Content Creation with Advanced Texturing, 360-Degree Modeling, and Interactive Editing

It isn’t easy to generate detailed and realistic 3D models from a single RGB image. Researchers from Shanghai AI Laboratory, The Chinese University of Hong Kong, Shanghai Jiao Tong University, and S-Lab NTU have presented HyperDreamer to address this issue. This framework solves this problem by enabling the creation of 3D content that is viewable,…

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Evaluating RAG Applications with RAGAs | by Leonie Monigatti | Dec, 2023

RAGAs (Retrieval-Augmented Generation Assessment) is a framework (GitHub, Docs) that provides you with the necessary ingredients to help you evaluate your RAG pipeline on a component level. Evaluation Data What’s interesting about RAGAs is that it started out as a framework for “reference-free” evaluation [1]. That means, instead of having to rely on human-annotated ground…

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