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Using Python ML for Predictive Analytics

This lab guides the student through Python examples that utilize metrics gathered from Prometheus. The Python Sci-Learn library is used for a Linear Regression example.

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Path Info

Level
Clock icon Beginner
Duration
Clock icon 1h 0m
Published
Clock icon Apr 05, 2019

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Table of Contents

  1. Challenge

    Install pip3.

    The command to install pip3 is:

    sudo apt install python3-pip
    
  2. Challenge

    Install Sci-Kit and Pandas Python modules.

    Use the pip3 command to install Sci-Kit Learn:

    pip3 install scikit-learn
    

    And:

    pip3 install pandas
    
  3. Challenge

    Review and run the check.py program.

    To review the code, you can navigate to the GitHub repository and view the check.py file. The link is:

    https://github.com/linuxacademy/content-aiops-essentials/blob/master/check.py
    

    The command to run the program is:

    python3 check.py
    
  4. Challenge

    Review and run the predictcpu.py and predictmem.py programs.

    To review the programs, you may use the following links:

    For predictcpu:

    https://github.com/linuxacademy/content-aiops-essentials/blob/master/predictcpu.py
    

    For predictmem:

    https://github.com/linuxacademy/content-aiops-essentials/blob/master/predictmem.py
    

    To run the programs, the command is:

    python3 predictcpu.py
    

    And:

    python3 predictmem.py
    
  5. Challenge

    Change the number of replicas to project.

    To change the number of replicas to project, edit the following file:

    [vi or nano] promql2.csv
    

    And then change the data column for replicas to the values you want to project.

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