University of Economics and Technology, Instructor
Director of Business Intelligence , CouponFollow
Senior Data Engineer, Publicis Sapient
Dev Advocate, Pinecone and Freelance ML
MLOps Project-Deploy Machine Learning Model to Production Python on AWS for Customer Churn Prediction
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Business Overview
Churn rate, also known as turnover or customer churn, is the rate at which a customer suspends a transaction with a company. Most commonly, it is expressed as the percentage of service subscribers who canceled their subscription within a certain time period. In this project, We aim to deploy a model which predicts whether the customer is going to churn in the near future or not. Amazon Web Services(AWS) is used as a cloud provider. We would advise you to have a basic understanding of Customer Churn Prediction Analysis using Ensemble Techniques before jumping into this project.
Aim
To deploy a model on AWS which predicts whether the customer is going to churn in the near future or not.
Tech Stack
➔ Language: Python
➔ Libraries: Flask, gunicorn
➔ Services: Flask, Docker, AWS, Gunicorn, Terraform
Prerequisites
It is advisable to have a basic knowledge of the following services to get an understanding of the project.
Flask
Terraform
AWS s3
Aws ECR
AWS ECS
AWS EC2 Load balancer
AWS Code commit
AWS Code Build
AWS Code Deploy
AWS Code Pipeline
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