machine learning model top of docker

1. configure yum for docker

cd /etc/yum.repos.d/

vim docker.repo

[docker]
baseurl = https://download.docker.com/linux/centos/7/x86_64/stable/
gpgcheck = 0
name = this is my docker

yum install docker-ce — nobest -y

it will install docker

2.launch docker

docker pull centos:latest

docker run -it — name=os1 centos:latest

it will launch one centos name os1

lets install python3 top of docker

1.yum install python3 -y

2.pip3 install pandas matplotlib joblib sklearn

lets create a linear regression model on top of docker

import pandas
dataset=pandas.read_csv(‘Salary_Data.csv’)
x=dataset[‘YearsExperience’]
y=dataset[‘Salary’]
x=x.values #converting into numpy format because we
x=x.reshape(30,1) #need a 2-D data from sklearn.linear_model import LinearReg
from sklearn.linear_model import LinearRegression
model=LinearRegression()
model.fit(x,y)
import joblib
joblib.dump(model,’mymodel.pk1')

it will create a model and save in mymodel.pk1

here we calculate intercet of model and cofficent