For installing the docker, I'm using the REDHAT 8 operating system. By default the REDHAT 8 doesn't come with the docker software. So first we have to download the docker software in side the REDHAT 8.
For this we have to configure the yum repository.
First of all login with root account and then go to:
-> cd /etc/yum.repos.d/
Create the file for docker repo with any name. The extension of file should be repo only.
Then open the vim editor with file that you have created .then write the code that are given below:
Now update the yum repository using command:
-> yum repolist
Now Download the docker-ce software that is community version. Use command –
yum install docker-ce –nobest
After installing docker if we check docker is install or not then run the command:
-> rpm -q docker-ce (it will show the software name )
Now start all the services of Docker through the below command:
->systemctl enable docker
If we check the status of the docker then run the command:
->systemctl status docker
Now we can move towards deployment of ML Model. So let's pull a centos docker image for building own docker image top of it.
->docker pull centos:latest
To check the images, run the below command, you can see your all the docker images like this:
Then we have to start our docker using the command:
-> docker run -i -t centos:latest
Then it will gives us new terminal for centos like this:
Then inside the docker container we have to deploy our ML model
For this we have install the python and the libraries that are require for our ML model.
First inastall the python using the command:
-> yum install python3
Then we have to install the libraries using the command:
->pip3 install numpy
->pip3 install pandas
->pip3 install scikit-learn
For ML model we require the data set.so for this we have to transfer or import the data set from the base operating system(REDHAT 8) to docker container.
For this we have to use the command:
-> docker cp (file name) (image name of container):/
Here the command will be:
-> docker cp SalaryData.csv busy_Matsumoto :/
After writing the code in vim editor we have to run the command in docker container.so for that we have to use the command:
-> python3 (file name)
-> python3 salary.py
Like this we have run the ML model inside the docker container.
Hopefully, you enjoy it