Machine Learning Platform (MLP) is a unified set of products for developing and operating the machine learning systems at the various stages of machine learning life cycle. The typical ML life cycle can be viewed through the following nine stages:
MLP Products are systems and services that are specifically built to solve one or multiple stages of the machine learning life cycle's problems. Currently, we have published the following MLP products:
- Feast - For managing and serving machine learning features.
- Merlin - For deploying, serving, and monitoring machine learning models.
- Turing - For designing, deploying, and evaluating machine learning experiments.
The MLP Server provides REST API used across MLP Products. It exposes a shared concepts such as ML Project. This repository also hosts Go and React (@gojek/mlp-ui) libraries used to build a common MLP functionailty.
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MLP uses Google Sign-in to authenticate the user to access the API and UI. After you get the client ID, specify it into
OAUTH_CLIENT_IDin.env.developmentfile.
If you already have Docker installed, you can spin up MLP and its dependencies by running:
docker-compose upMLP will now be reachable at http://localhost:8080.
To build and run MLP from the source code, you need to have Go, Node.js, and Yarn installed. You will also need a running Postgresql database. MLP uses Docker to make the task of setting up databases a little easier. You can run make local-db to starting up a Postgres Docker container.
mkdir -p $GOPATH/src/github.com/gojek
cd $GOPATH/src/github.com/gojek
git clone [email protected]/gojek/mlp.git mlp
cd mlp
make local-db
makeGo to the docs folder for the full documentation and guides.
For more information on building, running, and developing the UI app and library, see the UI's README.md.