Learn to implement a Deep Convolutional Generative Adversarial Network (DCGAN) in PyTorch through this comprehensive tutorial video. Explore the fundamentals of GANs, delve into the original GAN and DCGAN papers, and follow step-by-step instructions to build a DCGAN model trained on the MNIST dataset for generating new digits. Gain insights into discriminator and generator implementation, network initialization, dataset preparation, hyperparameter tuning, and the training process. Visualize results and understand key concepts in generative adversarial networks. Access additional resources, including a GAN playlist and recommended papers, to deepen your understanding of this powerful machine learning technique.
Overview
Syllabus
- Introduction
- Overview of the idea behind GANs
- Original GAN paper overview
- DCGAN paper overview
- Implementation of the Discriminator
- Implementation of the Generator
- Initialization of the network, dataset and hyperparameters
- Setting up the training phase
- Training the Network and visualizing results
Taught by
Aladdin Persson
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