Senior Data Scientist, Mawdoo3 Ltd
Data Engineer - Capacity Supply Chain and Provisioning, Microsoft India CoE
Chief Scientific Officer, Machine Medicine Technologies
Senior Data Engineer, Slintel-6sense company
In this AWS MLOps project, you will learn how to deploy a classification model using Flask on AWS.
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Each project solves a real business problem from start to finish. These projects cover the domains of Data Science, Machine Learning, Data Engineering, Big Data and Cloud.
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Each project comes with verified and tested solutions including code, queries, configuration files, and scripts. Download and reuse them.
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Business Objective
MLOps is a means of continuous delivery and deployment of a machine learning model. Practicing MLOps means that you advocate for automation and monitoring at all steps of ML system construction, including integration, testing, releasing, deployment, and infrastructure management.
In this project, we will be deploying the machine learning application for the Build Classification Algorithms for Digital Transformation [Banking]. Hence it is advised to go through this project first before. This project uses Amazon EKS (cloud platform), Amazon EC2, Elastic Load Balancing, etc services. Amazon EKS is a fully managed service that makes it easy to deploy, manage, and scale containerized applications using Kubernetes on AWS.
Aim
Deploy a machine learning model to identify the potential borrower customers to support focused marketing and deploy them through a cloud provider (AWS)
Tech stack
Prerequisites
It is advisable to have a basic knowledge of the following services to get an understanding of the project.
Approach
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