Machine learning inside Docker

Creating ML program inside docker

Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.

Here, in this blog I am going to run Machine Learning program inside docker and follow the steps :-

• Pull the Docker container image of CentOS image from Docker Hub and create a new container
• Install the Python software on the top of docker container
• In Container we need to copy/create machine learning model

Step 1.:- To install docker first, as I am running the program inside RedHat as base OS, so in order to install Docker first configure docker repo and the run the command,

yum install docker-ce -y

docker-install

Next I have to start docker services,

systemctl start docker

systemctl enable docker

docker-start-service

Step 2. :- Next step is to pull docker image from docker hub, here I am going to pull centos, run following command

docker pull centos:7

docker-images

Step 3. :- Now, we will start docker container

docker run -it — name <<container_name>> <<image_name:image_tag>>

docker-run

A brand new OS will be launched …

Step 4. : We will install Python inside docker,

yum install python3 -y

installing-docker-inside-python

and then installing python required modules using pip command

pip3 install pandas scikit-learn

docker-install-py-libraries

Step 5. :- Now, I am going to write Python Program for Simple Linear Regression.

where my dataset is SalaryData.csv which basically number of years experience and salary.

Simple-linear-regression-program

Now, At last Let’s run the program

running-py-program

And we can see that our model with the name “marks.pk1” is created, and our model is successfully created.

That’s all from my side.

Any query & suggestions, most welcome.

Keep Learning, keep growing.

Thank you ;)