SensiML Analytic Suite Python client
Project description
SensiML python client provides access to SensiML Analytics services for building machine learning pipelines including data processing, feature generation and classification for developing smart sensor algorithms optimized to run on embedded devices.
Installation
Download the Analytic Studio which will install a python 3 environment along with all the requirements to run the SensiML Library.
You can also install directly from pypy repository using pip. We recommend having python >= 3.7
pip install sensiml -U
Our library is designed to be used within a jupyter notebook. For our GUI to work correctly you will need to also install nbextension to jupyter notebook. Installation instructions can be found here
https://jupyter-contrib-nbextensions.readthedocs.io/en/latest/install.html
You will need to enable the following extensions. bqplot, ipywidgets and qgrid.
jupyter contrib nbextension install –user
jupyter nbextension enable bqplot
jupyter nbextension enable ipywidgets
jupyter nbextension enable qgrid
Connect to SensiML Analytic Engine
Once you have installed the software, you can connect to the server by running the following in a notebook cell.
from sensiml import *
sml = SensiML()
Connecting to SensiML servers requires and account, you can register at https://sensiml.cloud/accounts/register
Documentation can be found here https://sensiml.atlassian.net/wiki/spaces/SS/overview as well as in the Analytic Studio.
For information about SensiML, to get in touch, or learn more about using our platform to build machine learning models suitable for performing real-time timeseries classification on embedded devices you can reach us at https://sensiml.com/#contact
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