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Machine Learning Model Server on Redis

Redis-ML is a Redis module that implements several machine learning models as Redis data types.

The stored models are fully operational and support the prediction/evaluation process.

Redis-ML is a turnkey solution for using trained models in a production environment. Load ML models from any platform, immediately ready to serve.

Primary Features

  • Decision Tree ensembles (random forests) classification and regression
  • Linear regression
  • Logistic regression
  • Matrix operations

Building and Running

  1. Build a Redis server with support for modules (currently available from the unstable branch).

  2. You'll also need a BLAS library such as ATLAS. To install ATLAS:

  3. Ubuntu:  sh sudo apt-get install libatlas-base-dev

  4. CentOS/RHEL/Fedora:  sh sudo yum install -y atlas-devel atlas-static ln -s /usr/lib64/atlas/libatlas.a /usr/lib64/libatlas.a ln -s /usr/lib64/atlas/libtatlas.so /usr/lib64/libcblas.a

  5. Build the Redis-ML module:

sh git clone https://github.com/RedisLabsModules/redis-ml.git cd redis-ml/src make

  1. To load the module, start Redis with the --loadmodule /path/to/redis-ml/src/redis-ml.so option, add it as a directive to the configuration file or send a MODULE LOAD command.

Contributing

Issue reports, pull and feature requests are welcome.

License

AGPLv3 - see LICENSE