Category: recommendation-system
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Why MAP and MRR Fail for Search Ranking (and What to Use Instead)
Why MAP and MRR Fail for Search Ranking (and What to Use Instead) MAP and MRR look intuitive, but they quietly break ranking evaluation. Here’s why these metrics mislead—and how better alternatives fix it. The post Why MAP and MRR Fail for Search Ranking (and What to Use Instead) appeared first on Towards Data Science.…
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Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2
Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2 Deploying a FastAPI + PostgreSQL recommender system as a web application on Render The post Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2 appeared first on Towards Data Science. Lucas See Go to original source
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Building Video Game Recommender Systems with FastAPI, PostgreSQL, and Render: Part 1
Building Video Game Recommender Systems with FastAPI, PostgreSQL, and Render: Part 1 Designing a video game recommendations service with Steams API The post Building Video Game Recommender Systems with FastAPI, PostgreSQL, and Render: Part 1 appeared first on Towards Data Science. Lucas See Go to original source
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Connecting the Dots for Better Movie Recommendations
Connecting the Dots for Better Movie Recommendations Connecting the Dots for Better Movie Recommendations: Lightweight graph RAG on Rotten Tomatoes movie reviews The post Connecting the Dots for Better Movie Recommendations appeared first on Towards Data Science. Brian Godsey Go to original source
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LyRec: A Song Recommender That Reads Between the Lyrics
LyRec: A Song Recommender That Reads Between the Lyrics This is how I built an emotionally intelligent LLM-powered song recommendation system. Photo by David Pupăză on Unsplash Do you remember the last time you found yourself obsessing over a song? Maybe it was the raw emotion that resonated with you, or perhaps it was the lyrics…
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AI-Powered Information Extraction and Matchmaking
AI-Powered Information Extraction and Matchmaking Developing an application for extracting key profile information from CVs and recommending jobs aligned with the profile Continue reading on Towards Data Science » Umair Ali Khan Go to original source
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Ranking Basics: Pointwise, Pairwise, Listwise
Ranking Basics: Pointwise, Pairwise, Listwise Because thy neighbour matters Image taken from unsplash.com First, let’s talk about where ranking comes into play. Ranking is a big deal in e-commerce and search applications — essentially, any scenario where you need to organize documents based on a query. It’s a little different from classic classification or regression problems. For…
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AI, My Holiday Elf: Building a Gift Recommender for the Perfect Christmas
AI, My Holiday Elf: Building a Gift Recommender for the Perfect Christmas How I used AI and Streamlit to create a festive and fun gift recommendation app Continue reading on Towards Data Science » Shuqing Ke Go to original source