Insuricare project - Creating a customer ranking system
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Updated
Sep 20, 2023 - Jupyter Notebook
Insuricare project - Creating a customer ranking system
An attempt at building a Linear LETOR system.
Rank Aggregation in Phenotypic Selection
基于Elasticsearch构建智能化搜索应用
Machine learning course projects
This repository consist code for my deployed project about multi-stage recommendation. Two stages processing are used to generate a better recommendation for users, which are candidate retrieval and learning to rank algorithm.
Using Machine Learning to rank a list of customers most likely to buy a Car Insurance for a cross-sell campaign.
Insuricare Learning to Rank project app
Legal case retrieval challenge. Solution based on similarity search and learning-to-rank methods
Pytorch implementation of LEON: A New Framework for ML-Aided Query Optimization.
A library for the collection of common low-level features used in learning-to-rank algorithms.
This project aims to order a potential client list by propensity score.
(projeto ainda não finalizado) - Este repositório contém um projeto de uma seguradora deseja começar a vender seguro de veículos para clientes que já possuem plano de saúde.
A 'Learning to Rank' (LETOR) search engine built completely from scratch over the Wikipedia corpus
A neural network based learning-to-rank library.
CS 276 - Programming Assignment 4
Add a description, image, and links to the learning-to-rank topic page so that developers can more easily learn about it.
To associate your repository with the learning-to-rank topic, visit your repo's landing page and select "manage topics."