Deploying Simple Machine Learning Model inside Docker Container
As part of the MLOPS Summer Internship,
Here is the first task that was given to us:
#Task1 👨🏻💻 #MLOps_Summer2021
Task Description 📄
👉 Pull the Docker container image of CentOS image from Docker Hub and Create a new container
👉 Install the Python software on the top of the docker container
👉 In Container you need to copy/create a machine learning model
So let's begin the demonstration.
1. Installing docker in base OS:
Here I'm using RHEL8 and I have already installed docker.
2. Pulling the Centos image from docker hub
By using docker pull and then image name command I have pulled centos images
We can also see the available images with us using the docker images command.
3. Launching a Docker container using the centos image
We can see all the running container details using the docker ps command
By using docker run -it --name mlindocker centos command we launched docker container with centos image and with container name as mlindocker.
4. Copying the dataset into the container
By using cp we copied the dataset file into docker
5. Installing python3 software inside the docker container
6. Installing the necessary libraries (numpy, pandas, scikit-learn) using pip3
pip3 install numpy
pip3 install pandas
pip3 install scikit-learn
7. Writing the ML code
First, let's see the code in jupyter notebook
Let's write the same code in the container also
Now we are set to run the model file
As we can see when we enter the number of years of experience the ML model is giving the expected salary.
Github_link: https://github.com/manibhargava4/MLOPS_Internship_Task_1.git
