Machine Learning Time-series Platform

System dependencies:

If you are using Anaconda, create your environment with packaged dependencies pre-installed to save time:

conda create -n mltp scipy pandas matplotlib scikit-learn pytables pip

Then activate it:

source activate mltp

• Dependencies are listed in requirements.txt. Install them using:

  pip install --find-links=http://wheels.scikit-image.org -r requirements.txt

• Install and configure Disco

  Requires: Erlang. If you see errors about escript below, this is what you're missing.

  git clone --depth 1 git://github.com/discoproject/disco.git disco
  cd disco
  make
  cd lib && python setup.py install && cd ..
  

  Launch Disco using: bin/disco nodaemon

  Navigate to localhost:8989, click "configure" and ensure that an entry for "localhost" exists under "Available nodes". If not, add one with the corresponding number of cores as the "workers" value.

• Install RethinkDB

  For Debian / Ubuntu:

  source /etc/lsb-release && echo "deb http://download.rethinkdb.com/apt $DISTRIB_CODENAME main" | sudo tee /etc/apt/sources.list.d/rethinkdb.list
  wget -qO- http://download.rethinkdb.com/apt/pubkey.gpg | sudo apt-key add -
  sudo apt-get update
  sudo apt-get install rethinkdb
  

  Run rethinkdb in the MLTP directory.

• Install Docker

  Build the required images from Docker files by running

  tools/build_docker_images.sh

• Install nginx

Configuration

• In the file cfg.py, locate the following variables and set them to reflect your system architecture:

  PROJECT_PATH

  Optionally, also set

  MODELS_FOLDER, UPLOAD_FOLDER, FEATURES_FOLDER, ERR_LOG_PATH

Starting the application

First, initialize the database:

PYTHONPATH="." python flask/flask_app.py --db-init

Invoke the app either in standard mode or in debug mode:

PYTHONPATH="." python flask/flask_app.py

or

PYTHONPATH="." python flask/flask_app.py --debug

To specify host, port, etc., execute with --help for more information.