Deploying a Machine Learning Model in a Docker Container

Summer Program 2021 — #Task1

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.

GitHub repo: https://github.com/Ravenblaze128/Summerprogram-lw/tree/main/Task1

We are provided with a dataset which is filled with historical data/ observations.

Step 1: Write a code to train the model and get a prediction
https://github.com/Ravenblaze128/Summerprogram-lw/blob/main/Task1/Salary_LinearRegression.ipynb

Step 2: Check if the Docker is available or not

docker info

if unavailable, use

yum install docker-ce

Step 3: Download CentOS latestimage from Docker Hub

docker pull centos:latest

Step 4: Create a Container with the help of CentOS image

docker run -i -t — name=<name> centos:latest

Step 5:Download Python in the Container

yum install python3

Step 6: Install the Necessary libraries for the Python

pip3 install numpy
pip3 install pandas
pip3 install scikit-learn

Step 7: Copy the ML Model from the host to the container

while at host, use below command twice to copy the model and .csv file, by changing the names.

docker cp <model_name> <container_name>:/<model_name>

Step 8: Create a Model file

log back to the container terminal by using the command

docker attach <ContainerName>

and open a vi editor with .py ext.,

Esc-> :wq to save & exit the editor

Step 9: Run the Model

Run the model by using the command,

python3 model.py

Type in the Number of years of Experience,

The result!!

That’s all Folks!