Machine Learning Models deployment inside Docker Containers ??

Machine learning = Machine learning (ML) is a branch of artificial intelligence (AI) that focuses on building applications that can automatically and periodically learn and improve from experience without being explicitly programmed.

Docker = Docker is an open platform for developing, shipping, and running applications. Docker enables you to separate your applications from your infrastructure so you can deliver software quickly. With Docker, you can manage your infrastructure in the same ways you manage your applications.

Task Description ??

?? Pull the Docker container image of CentOS image from DockerHub and create a new container

?? Install the Python software on the top of docker container

?? In Container you need to copy/create machine learning model which you have created in jupyter notebook

?? Create a blog/article/video step by step you have done in completing this task. 

?? Submit the link of blog/article or video 

To pull centos docker image:

 docker pull centos

To create a new container:

docker run -it --name=summerinternship centos

To install python software on the top of docker container:

yum install python3

To copy code from base os to docker container: (note = here summerinternship2021 is folder in the base os which contains all the dataset and jupyter machine learning model code for those dataset. For reference you can check it from my github link provided with this blog.

docker cp summerinternship2021 summerinternship:/

To confirm dataset in docker container:

vim 50_Startups.csv