Module - 5 : ML using Jupyter Notebooks on Ceph#

Module Agenda

  • In this module, you will be creating a model using data stored in Ceph to detect the sentiment of customer trip reports, and uploading the trained model back to Ceph

Prerequisite

  • You need to have completed Modules 1-3 before beginning this module

  • The instructions for this excercise are available as Juypter Notebook (.ipynb) that you can download from here (Right click >> Save Link As ipynb)

  • An active JupyterHub instance is required to open this notebook. Use the JupyterHub application that you have deployed in module-2.

  • Login to the OpenShift Container Platform Console and click on the JupyterHub application endpoint URL from the Overview screen.

  • Use the following credentials to login into the JupyterHub application
    User Name : user1
    Password : 79e4e0

Important

If JupyterHub did not deploy cleanly, refer to the troubleshooting steps in Module 2 to redeploy.

  • Click the Upload button to the right

  • Find the Ceph_Data_Show_Lab_2.ipynb downloaded at the start of this module and upload it to JupyterHub

  • Click on the Upload button to finish uploading the notebook to JupyterHub

  • Select the Ceph_Data_Show_Lab_2.ipynb notebook to begin building a model for machine learning

  • Review the section Access Ceph Objbect Storage over S3A, the configuration here should look like this

  • Before running any of the cells in the notebook, select the first cell (the beginning of the notebook). Once the first cell is selected, click the Run button in the toolbar on each cell, stepping through the notebook and its results

End of Module

We have reached the end of Module-5. In this module, you created a machine learning model using data stored in Ceph and uploaded the model to Ceph for future use.