mlopstask3

DOCUMENTATION: This project is based on integration of GIT+DOCKER+JENKINS+ML, Finally we can say ML+DEVOPS=MLOPS project. 1.create container image that has python3 and keras or numpy installed using dockerfile. 2.when we launch this image, it should automatically starts train the model in the container. 3.create a job chain of job1,job2,job3,job4,and job5 using buildpipeline plugin in jenkins. 4.job1:Pull the Github repo automatically when someone developers push repo to Github. 5.job2: By looking at the code or programfile ,Jenkins should automatically start the machine learning software installed interpreter install image container to deploy code and start training. I used a pretrained lenet_mnist code or model (CNN) . 6.job3: Train your model and predict accuracy or metrics I found 98% accuracy for my lenet_mnist pretrained model. 7.job4: If metrics or accuracy is less than 98% ,then tweak the ML model architecture for this I increased a number of epochs from 2 to 4 .so, the accurac...