Semi-Supervised Learning with GANs

Explore semi-supervised learning with generative adversarial networks (GANs) in this 34-minute video tutorial. Learn how to train models using a combination of labeled and unlabeled images, making it ideal for large datasets with partial labeling. Discover the differences between regular GANs and semi-supervised GANs (SGANs), including the dual training of the discriminator for both unsupervised feature learning and supervised class labeling. Understand why SGANs can achieve better accuracy with limited labeled data compared to traditional convolutional neural networks (CNNs). Dive into topics such as multiclass classification, model definition, and the training process. Gain insights from relevant research papers and resources to deepen your understanding of this powerful machine learning technique.

Introduction
Semisupervised learning
Amnish classification
Model definition
Semisupervised GAN
Multiclass GAN
Summary
Training