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When (Not) to Use Vector DB

When (Not) to Use Vector DB

by Dr. Owns | Dec 16, 2025 | Analytics, Artificial Intelligence, Data and Information, Decision Support

When indexing hurts more than it helps: how we realized our RAG use case needed a key-value store, not a vector database The post When (Not) to Use Vector DB appeared first on Towards Data Science. ​When indexing hurts more than it helps: how we realized our RAG use...
When (Not) to Use Vector DB

Separate Numbers and Text in One Column Using Power Query

by Dr. Owns | Dec 16, 2025 | Analytics, Artificial Intelligence, Data and Information, Decision Support

An Excel sheet with a column containing numbers and text? What a mess! The post Separate Numbers and Text in One Column Using Power Query appeared first on Towards Data Science. ​An Excel sheet with a column containing numbers and text? What a mess! The post Separate...
When (Not) to Use Vector DB

The Machine Learning “Advent Calendar” Day 16: Kernel Trick in Excel

by Dr. Owns | Dec 16, 2025 | Analytics, Artificial Intelligence, Data and Information, Decision Support

Kernel SVM often feels abstract, with kernels, dual formulations, and support vectors. In this article, we take a different path. Starting from Kernel Density Estimation, we build Kernel SVM step by step as a sum of local bells, weighted and selected by hinge loss,...
When (Not) to Use Vector DB

Lessons Learned After 8 Years of Machine Learning

by Dr. Owns | Dec 16, 2025 | Analytics, Artificial Intelligence, Data and Information, Decision Support

Deep work, over-identification, sports, and blogging The post Lessons Learned After 8 Years of Machine Learning appeared first on Towards Data Science. ​Deep work, over-identification, sports, and blogging The post Lessons Learned After 8 Years of Machine Learning...
When (Not) to Use Vector DB

The Machine Learning “Advent Calendar” Day 15: SVM in Excel

by Dr. Owns | Dec 15, 2025 | Analytics, Artificial Intelligence, Data and Information, Decision Support

Instead of starting with margins and geometry, this article builds the Support Vector Machine step by step from familiar models. By changing the loss function and reusing regularization, SVM appears naturally as a linear classifier trained by optimization. This...
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