RUNNING ML CODE ON THE TOP OF CONTAINER !

Task discription :-

👉 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.

👉 Run the Machine learning code on top of the container.

Task

Start the Services Of Docker !

# systemctl start docker

Pull the Centos image From DockerHub!

# docker pull centos:latest

Launch container With name mlos

# docker run -it --name mlos centos

Now if you have data in windows then we can transfer that usin winscp to the linux vm system !

Copy the Dataset file in created container’s / folder

# docker cp SalaryData.csv mlos:/

Install python3 in container

# yum install python3

Install numpy, pandas and sklearn library using pip3

# pip3 install numpy
# pip3 install pandas
# pip3 install sklearn

You can check by command

# pip3 list

Now, let us start writing the code in vi editor

# vi code.py

code is

import pandas
import numpy
from sklearn.linear_model import LinearRegression
db = pandas.read_csv("SalaryData.csv")
x = db['YearsExperience']
y = db['Salary']
x = x.values.reshape(30,1)
mind = LinearRegression()
mind.fit(x, y)
a = int(input(('Enter the years of experience gor which salary to be predicted: '))
ans = mind.predict([[float(a)]])
print(ans)

Task Competed !