Machine Learning Model inside Docker
What is Machine Learning?
In simple words, Machine Learning is the concept which includes different types of algorithms through which we provide intelligence to a machine to work/predict something on itself on a particular dataset
What is Docker?
Docker is a platform in which it provides various operating systems so that the manual time required to install an operating system and then log in as a user and after that we open an application, is reduced to seconds with the use of docker as it provides operating system then and there and downloads it and installs within seconds
First of all we will upload our machine learning model file and dataset file on Github so that it makes easy for us to fetch the files from there with the help of cloning
We will open Redhat Linux in our VM and through ifconfig command , will note the IP of our user in Redhat
Download and install Putty(Generally used for connecting with another operating system and SSH provides a secure, encrypted connection to the remote system) and then type the IP which you noted in the previous step
After that it will open a terminal in which it will prompt for the username and password of your Redhat Linux user, enter it and then your redhat system will be opened in this terminal, prompting with
[root@localhost `]#
Create a workspace for yourself, here I have done the same by creating a directory named as ML for cloning the files from github
Clone the necessary files for running our model from github repository to the ML directory
Here we can see that .csv file as dataset and .pk1 as our model has been successfully copied in our ML directory
Now, we will focus on installing docker on our system
Navigate to /etc/yum.repos.d for creating a docker.repo file so that when we provide command for docker installation as yum install docker-ce then the system will check in yum.repos.d in all the .repo file for the url for downloading and installing docker from that url
Installing vim editor for writing code inside docker.repo file
Create a file with
vim docker.repo
Inside docker.repo , write the above codes for successful installation of Docker and save the file with pressing Esc and then :wq
command for installing Docker and after that docker will be successfully installed in your Redhat
Start Docker
Use the command docker pull with os_name for installing the particular os/container or pulling the image file of that particular os/container, here I have pulled centos os
For running the os and giving name to the os as skos
Checking the os has been successfully installed or not
Now you are successfully inside your container/os
Install python with the above code inside your container/os
Install numpy, pandas & scikit-learn libraries from python for successfully training your machine learning model
Now copy your file required for machine learning model inside docker container using the following command
docker cp file_name os_name:/directory_path
checking for successful copy of files
Here I have created a python file model.py for running my machine learning model
vim model.py
code for running my model, here I have imported my model “salary.pk1” through joblib library and then saved it
Run the python file and here as you can see, my machine learning model is working perfectly fine and predicting the result for 15 years experience
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