Model Docker Container on AWS Cloud | Machine Learning Model Deployment pipeline | Part 1

The speaker discusses various tools for deploying machine learning models, including Docker, Flask, Streamlit, Heroku, and Django.
They mention AWS Elastic Beanstalk as a feature of AWS Cloud for model deployment and compare it to regular EC2 instances.
The speaker emphasizes the importance of avoiding deployment issues and suggests using Docker containerization to overcome dependency problems.
They explain the concept of containerization and how it differs from virtualization, highlighting Docker as a tool for creating and managing containers.
The speaker demonstrates the process of deploying a machine learning model using Docker and AWS Elastic Beanstalk, mentioning the steps involved and the benefits of automatic resource management.

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