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Updated 3 years ago
Generative Adversarial Modeling
Generative Adversarial Networks or GANs, use neural networks for a very different purpose: Generative modeling
Generative modeling is an unsupervised learning task in machine learning that involves automatically discovering and learning the regularities or patterns in input data in such a way that the model can be used to generate or output new examples that plausibly could have been drawn from the original dataset.
Most of the code in this tutorial is based on this notebook.
project_name = 'Generative Network'
# Uncomment and run the appropriate command for your operating system, if required
# No installation is reqiured on Google Colab / Kaggle notebooks
# Linux / Binder / Windows (No GPU)
# !pip install numpy matplotlib torch==1.7.0+cpu torchvision==0.8.1+cpu torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html
# Linux / Windows (GPU)
# pip install numpy matplotlib torch==1.7.1+cu110 torchvision==0.8.2+cu110 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html
# MacOS (NO GPU)
# !pip install numpy matplotlib torch torchvision torchaudio
Downloading and Exploring the Data
!pip install opendatasets --upgrade --quiet