Integration of Machine Learning with Devops

Problem statement : We have to create a machine learning project and automate this with the help of Devops .

A docker instance will run my ml code which will be downloaded from the github. We will train a machine learning model in the docker instance , after training we test the accuracy of the model and notify the developer through email. If the accuracy of the model is less than 80% , we have to tweak our code and retrain the model. All the task should be monitored.

To achieve this setup we will use jenkins as our automation tool.

We have to follow the steps to achive this task :

Step 1: create a dockerfile which will launch the docker instance

Step 2:Create a job to download github repository

Step 3: Identify the type of ml code i.e. it is deeplearning code or regression code etc and the launch the container with respective software . In my case it is cnn model.

Step 4: Check for accuracy

Step 5:Tweak the ml code if the desired accuracy is not achieved

Step 6:Notify the developer about the accuracy of the code

import smtplibs = smtplib.SMTP(‘’, 587)


s.login(“”, “*************”)

#Message that will be sent to

mailmsg = “accuracy is achieved” s.sendmail(“”, “”, msg)

#For terminating


Step 7:Monitoring

Here is my link to github:

please give your valuable suggestion about the project.

This is my first ever blog so please give your valuable feedback.

I would like to thank my mentor Mr Vimal Daga for guiding me throughout my learning journey of latest Technology.