@@ -4,7 +4,7 @@ We recommand to use the notebook (.ipynb) but the Python script (.py) is also pr
The purpose of this task is to explore Generative Adversarial Networks (GANs) and their implementation, specifically focusing on an architecture that enables image-to-image translation.
# Fake numbers generations
# Fake numbers generation
In the first part, we aim to learn and understand the basic concepts of Generative Adversarial Networks through a DCGAN and generate new handwritten numbers from the learned network after showing it real handwritten numbers.
