Automation Of Deep Learning With Jenkins
PROJECT Automation Of a Deep Learning Model Task Overview - Creating a Deep Learning Model to predict the objects of an image using Docker. This model will train automatically, when the Docker image is launched. Jenkins will automatically pull the repo when developer commits. Jenkins will automatically deploy the code and start training the model using CNN, Jenkins will automatically start the container required for processing. It will predict the accuracy of trained model. If the accuracy is less than 80%, then tweak the machine learning model the machine learning model architecture, retrain the model and send the notification on mail to Developer. A extra job is given to Jenkins to monitor the app container, If the container fails due to any reason Jenkins will automatically start the container again. Tools Used – · Jenkins · Git · ...