This course will teach you how to design, train, and evaluate generative models to create synthetic data and improve real-world ML workflows.
What you'll learn
Globomantics, a global logistics company, struggles with inconsistent shipment info and limited labeled data, making it difficult to detect damaged packages accurately.
In this course, Build a Generative AI Model, you'll gain the ability to design, train, and evaluate generative models that improve real-world machine learning workflows.
First, you'll explore how to construct and train autoencoders for unsupervised representation learning and data reconstruction.
Next, you'll discover how to extend these concepts into Generative Adversarial Networks (GAN) and stabilize their adversarial training.
Finally, you'll learn how to visualize latent spaces, generate synthetic samples, and evaluate overall model performance.