 As a developer intern in a software development company, I worked with machine learning. We had to achieve a specific accuracy level and it was quite challenging because the process was manual and it didn't need to be. To reach 85% of the accuracy, I had to train my model manually again and again by manipulating the number of epochs and adding multiple layers. This eats up a lot of system resources which was a major problem for any machine learning engineer. So, I built something which I call as the accuracy achiever. With the help of Jenkins, I only need to make a single commit code to the GitHub and everything is done automatically just with one click. Jenkins also made it possible to monitor the models which were running. If they fail, Jenkins automatically launches another and notifies the developer through email. The results were awesome. Jenkins allowed me to automate everything. That makes the model training much more easier. Using Jenkins, the system automatically manipulated the code and added some more layers and it helped me to achieve 89% of the accuracy which was way beyond expectations. And since it's a very efficient method, it's better use of system resources as well. I just love Jenkins. It has so many features and plugins. It makes everything possible and everything we can automate using Jenkins. Jenkins is the way to achieve accuracy in machine learning operations. With Jenkins, we can automate any machine learning operations to achieve accuracy.