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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.


pip install sensiml

jupyter contrib nbextension install –user

jupyter nbextension enable bqplot

jupyter nbextension enable ipywidgets

jupyter nbextension enable qgrid

or download the Analytic Studio

Connect to SensiML Analytic Engine

from sensiml import SensiML

sml = SensiML()

(Note: Connecting to SensiML servers requires and account to log in)

Go to to learn more about using our platform to build
machine learning models suitable for performing real-time timeseries classification on embedded devices.

Project details

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Filename, size & hash SHA256 hash help File type Python version Upload date
SensiML-2.4.1-py3-none-any.whl (177.5 kB) Copy SHA256 hash SHA256 Wheel py3
SensiML-2.4.1.tar.gz (100.8 kB) Copy SHA256 hash SHA256 Source None

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