Welcome to Machine Learning in Production’s documentation!¶
This documentation is meant to be a complementary material describing the implementation of our proof-of-concept project for the course Machine Learning in Production
Note
This project is a proof-of-concept, nevertheless, state-of-the-art tools and best practices has been followed during the development.
Danger
This project is not intended to be used in a REAL production system!
This project exploit the power of containers and the concept of microservices to build a distributed system. We use Docker to manage the containers and docker-compose to start and shutdown the entire system (for additional info see Docker).
We used open source software and made the deployment as plotform independent as possible.
Setup and installation commands are provided for Linux OS only.
Installation¶
Installation and execution is managed through the given docker-compose file.
Clone this repository, then build the container images using the docker-compose build command.
To run the application, use the docker-compose up -d command.
More details on the Docker page.
Components¶
Following an overview of all the components available in the application.