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TUD AIS

This package contains lab material for the module Angewandte Intelligente Signalverarbeitung offered by Professor Birkholz at TU Dresden.

Setup (Linux, Mac OS X, Windows)

To obtain the lab material, you can simply install the package just like any other Python package. We recommend setting up a virtual environment before installing. The steps to do so are as follows:

Step 0: Get Python

If you don't already have it installed, download and install the current version of Python for your platform.

Step 1: Set up your working directory

  1. Create a folder in a suitable location where all the lab material will be placed (e.g. C:\Users\MyUserName\Documents\TUD-AIS-Lab). Just to be safe, choose a path that is not too long and that does not contain spaces.

  2. Open a shell (Linux), terminal (Mac), or command prompt (Windows) and navigate to the created folder.

  3. Create a virtual environment called .ais-env by entering the following command:

    python -m venv .ais-env
  4. Activate the virtual environment by entering the following command depending on your operating system:

    Linux or Mac:

    source .ais-env/bin/activate

    Windows:

    .ais-env\Scripts\activate.bat
    

    You should now see the name of your environment showing up in parentheses at the beginning of the line: Screenshot showing the active virtual environment in the command prompt

    You can deactivate the virtual environment at any time by entering the command deactivate.

Step 2: Install the lab material

  1. Make sure that your virtual environment is active (see Step 1.4 above).
  2. Install the lab material by entering the following command:
    pip install tudais
    
    This will install all dependencies of the lab materials and the lab materials itself. It may take a while.

Step 3: Start the lab

  1. Make sure that your virtual environment is active (see Step 1.4 above).
  2. Enter the following command:
    tud-ais-start
    
    This will open your default web browser and show the root folder of the lab material.

Step 4: Have fun working through the notebooks

Some of the notebooks are explicitly structured and contain detailed instructions (code-along), while other notebooks are far less guided and offer an opportunity to apply your acquired knowledge (hands-on).

The recommended order of tackling the notebooks is as follows:

  1. preprocessing/Lego-Sets/Lego Sets Preprocessing.ipynb (code-along)
  2. classification/Wine-Quality/Klassifikation von Wein.ipynb (code-along)
  3. regression/Wine-Alcohol/Vorhersage des Alkoholgehalts von Wein.ipynb (code-along)
  4. classification/Titanic/Untergang der Titanic.ipynb (hands-on)
  5. regression/House-Prices/Vorhersage von Immobilienpreisen.ipynb (hands-on)

Step 5: Submit the completed material

Once you have completed the material, you may submit your solution for credit or qualification purposes.

  1. Make sure that your virtual environment is active (see Step 1.4 above).
  2. Enter the following command:
    tud-ais-prepare-submission
    
    When prompted, enter your personal information. This will create a ZIP archive with all required files.
  3. Send the ZIP archive to your lab supervisor via email.

If you run into any problems in this process, contact Christian Kleiner for assistance.

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Supplemental material for the lecture Angewandte Intelligente Signalverarbeitung at TU Dresden

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