Category: Applied Analytics
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I built a multi-model orchestrator system to solve complex problems, since we know two or more heads think better than one. Plus, seeing them correct each other reveals the weaknesses of each one. Following my previous article, where I had them debate who would be the next world soccer champion, many ideas came up about…
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After a long debate, I think I finally know who’s going to win the FIFA World Cup 2026. This weekend I finished an idea I’d been sitting on for a few months: getting four different LLMs to debate a specific topic within a defined set of guidelines. So I took ChatGPT, Claude, Gemini and Grok,…
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If you work in a BI team and you are still creating insights manually using tools like Power BI, or Tableau, stay here, this article might be interesting for you. Over the last few months, I’ve been very curious about how LLMs can be used to automate business processes. So, in this article, I decided…
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1. predicting sentiment from amazon reviews I’ve always been fascinated by how platforms try to understand what we like. Years ago, Netflix used a simple star-rating system to recommend movies and shows, and it felt almost magical that a handful of stars could shape your entire watchlist. Behind the scenes, they were likely running some…
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Introduction In this project I set myself a very practical goal: build a daily forecasting model for steel rebar prices and turn it into a reproducible, end-to-end workflow that I can run in Python and later expose through an API. Steel is a core input for construction and infrastructure, and even small moves in its…
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Understanding Customer Behavior Through K-Means Clustering: A Practical RFM Approach The goal of this project is to use the Online Retail II dataset to build a K-means model capable of revealing natural patterns in customer behavior, without relying on predefined labels or assumptions. My intention is to understand how customers group themselves based on their…