The SensiML Python SDK provides a 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/Setup Instructions
The SensiML Python SDK requires python version 3.7 or greater to be installed on your computer.
We recommend running the SensiML Python SDK using Jupyter Notebook. Install Jupyter Notebook by opening a command prompt window on your computer and run the following command
pip install jupyter
Next, to install the SensiML Python SDK open a command prompt window on your computer and run the following command
pip install SensiML
This command will install the SensiML Python SDK and all of the required dependencies to your computer.
Connect to SensiML Cloud
Once you have installed the software, you can connect to the server by running the following
from sensiml import *
client = SensiML()
Connecting to SensiML servers requires and account, you can register at https://sensiml.com
Documentation can be found here https://sensiml.com/documentation/
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Release files for sensiml-dev 2023.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sensiml-dev-2023.1.2.tar.gz | 131.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sensiml_dev-2023.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 311.2 kB
Release files / sensiml-dev-2023.1.2.tar.gz
| Download URL | sensiml-dev-2023.1.2.tar.gz |
|---|---|
| Size | 131.1 kB |
| Tags | Source |
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| Upload date | |
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No |
| Uploaded via |
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Release files / sensiml_dev-2023.1.2-py3-none-any.whl
| Download URL | sensiml_dev-2023.1.2-py3-none-any.whl |
|---|---|
| Size | 180.2 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.10
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