Machine Learning In Application

Practical implemantation of Machine Learning in the Application.

Architecture

• Model: Machine Learning Model
• Trainer: Training the model. So training process (loss, optimizer) is separated from Model.
• Model API: Interface between the Model and Application.
• DataProcessor: Load the data and preprocess it. It is used in Trainer and ModelAPI.
• Resource: It manages the parameters for Trainer, Model and DataProcessor.

Demo Application

handwritten number recognizer by Chainer.

You can deploy this application by docker.

Please refer this tutorial to deploy the application.

• heroku plugins:install heroku-container-registry
• heroku container:login
• git clone https://github.com/icoxfog417/machine_learning_in_application.git
• heroku create
• heroku container:push web
• heroku open