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SensiML Analytic Suite Python Dev Client

Project description

SensiML python client provides programmatic interface to SensiML REST API’s 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.

https://sensiml.com/download/

You can also install directly from pypy repository using pip. We recommend having python >= 3.7

pip install sensiml

pip install sensiml_widgets -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 –sys-prefix

jupyter nbextension enable –sys-prefix bqplot

jupyter nbextension enable–sys-prefix ipywidgets

jupyter nbextension enable –sys-prefix 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 *

dsk = SensiML()

Connecting to SensiML servers requires and account, you can register at https://sensiml.com

Documentation can be found here https://sensiml.com/documentation/ 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

Project details


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