Loud ML is the first open-source AI solution for ICT and IoT automation
Loud ML is an open source inference engine for metrics and events, and the fastest way to embed machine learning in your time series application. This includes APIs for storing and querying data, processing it in the background for ML or detecting outliers for alerting purposes, and more.
This page, as well as the rest of our docs, are open-source and available on GitHub. We welcome your contributions.
Loud ML is an open source time series inference engine built on top of TensorFlow. It's useful to forecast data, detect outliers, and automate your process using future knowledge.
loudmld can be installed using pip
similar to other Python packages. Do not use sudo
with pip
. It is usually good to work in a virtualenv or venv to avoid conflicts with other package managers and Python projects. For a quick introduction see Python Virtual Environments in Five Minutes
Run inside a virtualenv:
make install
You can start the Loud ML model server using:
systemctl start loudmld
if you have installed Loud ML using an official Debian or RPM package, and are running a distro with systemd
.loudmld
if you have built Loud ML from source.loudmld -c <path/to/config.yml file>
One extra package is needed to run the command line interface.
If you've installed loudml-python
locally, the loudml
command should be available via the command line. Executing loudml will start the CLI and automatically connect to the local Loud ML model server instance (assuming you have already started the server with systemctl start loudmld
or by running loudmld directly).
pip install loudml-python
The Python client library is open source
Contributors wanted! Official client libraries for Javascript, Java, Ruby, Go can be found at: https://github.com/loudml
make test
make clean && make rpm
make clean && make repo
If you're feeling adventurous and want to contribute to Loud ML, see our contributing doc for info on how to make feature requests, build from source, and run tests.
See LICENSE
Contact [email protected] to learn how we can best help you succeed.