Using Hotel Data to predict High Value And Potential VIP Guests

Last update: Feb 14, 2022

Related tags

Overview

Description

Using hotel data and AI to predict high value guests and potential VIP guests.

Hotel can leverage on prediction resutls to run more effective email marketing campaign, focus on the right target customers with only limited resources, and deliver better customer experiences.

Technology stack

Web/Frontend

Angular 11
Graphql
Lib: amchart, material, foundation

Server/Backend

Spring boot 2
graphql-java 11
Lib: graphql-java-tool, log4j, POI, commons-io, httpclient

AI Services

Python 3.8
Lib: Pandas, Featuretools, Scikit-learn, Numpy

Architecture

AI Pipeline Explanation

Demo

Video demo

Deployment

docker-compose up --build -d

Contributors

_{Duy Nguyen}

_{Hien Cao}

_{Quoc Nguyen}

_{Hai Vo}

_{Minh Nguyen}

_{Hoang Anh Nguyen}

MIT

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Comments

Bump httpclient from 4.5.6 to 4.5.13 in /services
Bumps httpclient from 4.5.6 to 4.5.13.

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dependencies
opened by dependabot[bot] 0
'Logout' button behavior issue

Scenario: https://lite.dataspire.io/home [Fri Sep 10 2021 20:16:51 GMT+0700]

[Reproduce Step]: Step 1: Load to first page (home page) Step 2: Check and hover on ‘Logout’ button before login/authorize.

[Result]: ‘Logout’ button is enabled and appear mouse pointer when hover on it.

[Expect]: If user don't authorize/login yet, the “Logout’ button should be disabled and should not display cursor pointer when hover.

opened by thanhptt0206 0

Owner

HCG

GitHub

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Using Hotel Data to predict High Value And Potential VIP Guests

Related tags

Overview

Description

Using hotel data and AI to predict high value guests and potential VIP guests.

Hotel can leverage on prediction resutls to run more effective email marketing campaign, focus on the right target customers with only limited resources, and deliver better customer experiences.

Technology stack

Web/Frontend

Server/Backend

AI Services

Architecture

AI Pipeline Explanation

Demo

Deployment

Contributors

You might also like...

A data-driven approach to quantify the value of classifiers in a machine learning ensemble.

A Simple Key-Value Data-store written in Python

Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

E2EC: An End-to-End Contour-based Method for High-Quality High-Speed Instance Segmentation

A package to predict protein inter-residue geometries from sequence data

Predict bus arrival time using VertexAI and Nvidia's Jetson Nano

Segcache: a memory-efficient and scalable in-memory key-value cache for small objects

PyTorch implementation of Value Iteration Networks (VIN): Clean, Simple and Modular. Visualization in Visdom.

Comments

Bump httpclient from 4.5.6 to 4.5.13 in /services

'Logout' button behavior issue

Owner

HCG

Rule based classification A hotel s customers dataset

This code is 3d-CNN model that can predict environmental value

Using machine learning to predict and analyze high and low reader engagement for New York Times articles posted to Facebook.

Neural Scene Flow Fields using pytorch-lightning, with potential improvements

Differentiable molecular simulation of proteins with a coarse-grained potential

CPF: Learning a Contact Potential Field to Model the Hand-object Interaction

Riemannian Convex Potential Maps

Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2

[ICCV 2021] Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation

A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.