Training a ML Model usin Docker Container

Description:

• Pulling a Docker image of CentOS from DockerHub and creating a new container.
• Launching the Docker container.
• Installing Python on top of the Docker container.
• Installing the required libraries for the machine learning model.
• Creating and running the Python code, and getting the desired output.

STEP 1:

• The first step is to check whether Docker is installed in the system or not. For installing Docker the command used is:- "yum install docker-ce".
• Checking the status of Docker if it's running or not, the command used is:- "systemctl status docker".
• Then pulling the Docker image of CentOS from DockerHub and creating a container.

• For launching the container the command used is:- "docker run -it --name <CONTAINER_NAME> <OS_NAME>:<version>".

STEP 2:

• Installing Python on top of the docker container using the command:- "yum install python 3".

STEP 3:

• Copying the data set from the local host (Base OS) to the Docker container on which we train the ML model.
• The command used for the above stated step is:- "docker cp <file_name> <container_name>:<dest>"

• Starting the container in Docker using the command:- "docker start <container_name>".

STEP 4:

• Installing the required libraries to load the Machine Learning model, the command used to install these libraries is:- "pip3 install <library_name>".

• Creating the Python code for prediction using Linear Regression.

• The output of the Machine Learning model:

I hope that this article helps in gaining an insight of how to train a ML model on Docker, and if there is any feedback please feel free to reach out.

Thank You.