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
POC of Learning to Rank with Opensearch
CS 276 - Programming Assignment 4
This repository contains files and script to develop an interest ranking algorithm, for an Insurance Company. The objective of the project is to reduce the time and costs associated with prospecting customers and, at the same time, increase revenue. (Student Project 4 / DS Community)
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