First and foremost, join us at GANs Workshop Slack Channel so that we can keep in sync. Most probably, this channel will be the starting point for a local community of developers interested in hands-on AI & ML stuff.

For this workshop we will use the MNIST and Celeba datasets. You can download them from this google drive folder. The folder contains the two img_align_celeba and mnist ziped folders. Please create a data folder in the project repository's root directory, copy the two dataset folders there and extract them.

The final paths relative to the project root should be: ./data/img_align_celeba and ./data/mnist.

We will be using the Anaconda platform for this workshop. Anaconda is a distribution of packages built for data science that comes with conda, a CLI packages and environments manager.

1. Install Conda CLI: we are mainly interested in conda, therefore you have two options:

• Install Miniconda - a mini version of Anaconda that includes only conda and its dependencies
  • Download the Python 3.6 installer for your OS from here and follow these instructions to install it.
• Install the entire Anaconda ecosystem which contains conda plus over 720 open source packages
  • Download the Python 3.6 installer for your OS and follow the instructions from here.

2. Update all the packages in the default root environment: conda upgrade --all

Most used commands:

• conda install package_name
• conda update package_name
• conda remove package_name
• conda search search_term
• conda list - list all installed packages

Most used commands:

• conda create -n env_name list_of_packages
• conda env export > environment.yaml - save packages to .yaml file
• conda env create -f environment.yaml - create env from yaml file
• source activate my_env (Mac/Linux) OR activate my_env (Windows) - activate environment
• source deactivate (Mac/Linux) OR deactivate (Windows) - deactivate environment
• conda env list - list all environments
• conda env remove -n env_name

For more info check this and this

For this workshop create a new environment using the provided gans_workshop.yaml by running:

• conda env create -f .environments/gans_environment_OS.yml

Activate the new created environment using:

• source activate gans_workshop (Mac/Linux)
• activate gans_workshop (Windows)

Then run the following command to start a test jupyter notebook:

• jupyter notebook GANsWorkshop.ipynb