Machine Learning Models inside Docker

NARMADA M
2 min readJun 20, 2021

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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. By taking advantage of Docker’s methodologies for shipping, testing, and deploying code quickly, you can significantly reduce the delay between writing code and running it in production.

Prerequisites: Docker should be installed and enabled

Pulling the Docker container image of CentOS from Docker hub

docker pull centos:8

Running the docker image

docker run -it — name C-os centos:8

Installing Python software

yum install python3

Installing Python Library

pip3 install numpy

pip3 install pandas

We can transfer the dataset from the Windows to the virtual machine by the software called as WinSCP

Editing the python code

vim xxx.py

Executing the python code

python3 xxx.py

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

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