Head of Data Science, Slated
Data and Blockchain Professional
Data Engineer - Capacity Supply Chain and Provisioning, Microsoft India CoE
Senior Data Engineer, Slintel-6sense company
Build and deploy ARCH and GARCH time series forecasting models in Python on AWS .
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Business Objective
Deployment is the method by which you integrate a machine learning model into an existing production environment to make practical business decisions based on data.
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 aim to create the MLOps project for the time series arch model Build ARCH and GARCH Models in Time Series using Python on the AWS cloud platform (Amazon Web Services) that is cost-optimized. Cost-optimized model deployment means that we will be using minimal services.
Aim
To create an MLOps project using the Amazon Web Services (AWS) platform to deploy the time series arch model in production.
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