Solutions
Machine Learning on LE via Jupyter
2min
- After Checkout, a tar.gz file is expected to be downloaded
- Log in to your LitmusEdge, Navigate to Applications -> Images
- Click on Upload Image and upload the tar file there
- Navigate to Applications -> Containers and enter the following command there:
- docker run -p 8888:8888 -v /var/lib/loopedge-analytics2/models/:/home/loopedge/work/notes/savedModels <imgName>:<tagName>
- Here we are asking the container to run on port 8888, with API token passed as an environment variable, and using imgName and tagName respectively
- We are also using -v to volume mount the savedModels folder to analytics, so that we can automatically get our saved model in analytics without any additional steps
- Access the application by going to a new tab in browser, and writing current LE IP address, followed by :8888
- for example if the application is running on an LE with IP address 10.17.10.27, one would type 10.17.10.27:8888 in a new tab of browser to access the application