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Jupyter Notebooks: Machine Learning

Notebooks for hands-on on machine learning supervised and unsupervised tasks.

Notebook list

  1. Hands-On 1: Python and Pandas Tutorial
  2. Hands-On 2: Unsupervised Learning
  3. Hands-On 3: Supervised Learning
  4. Hands-On 4: Model Selection

Setup Envornment on Windows

  1. Get the Anaconda (Individual Edition) here

  2. Install Anaconda on your machine. Pay attention when the installer asks for Register Anaconda3 as my default Python 3.8, untick it if you dont want to!

Create Virtual Environment

  1. Open Anaconda Navigator and select Environments on the left side panel

    import-example

  2. Click Import and use the environment.yml as specification File. Use mlenv as name for the environment

    import-example

  3. Once installed, go to the Home panel and be sure the installed environment is selected

    import-example

  4. Launch jupyter notebook and navigate to the repository folder

  5. Open the notebook you want to run

Setup Environment on Linux

Install miniconda

  1. Download miniconda the miniconda linux installer
  2. Follow instructions here for installing miniconda

Create Virtual Environment

To set up the conda environment with the required packages and running the notebooks, execute the following command:

  1. Create a new virtual environment: conda env create -n mlenv -f=./environment.yml

  2. Set up the environment: conda activate mlenv

  3. Run jupyter notebooks: jupyter notebook


Licence

the Creative Common BY-SA-4.0 licence

Except where otherwise noted, all content of this machine-learning-course-notebooks repository are distributed under the Creative Common BY-SA-4.0 licence

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Jupyter notebooks about machine learning supervised and unsupervised tasks

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