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Generative Models – Learning Outcomes

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By the end of this module, you will be able to:

Outline the landscape of machine learning
State the procedure for computing patterns in a dataset
Discuss the notion of various generative models in deep learning
Describe the process of training and evaluating various types of GANs
Explain the significance of variational autoencoders in deep generative models
Identify the procedure for improving the image quality by mapping VAEs and GANs
Recognize the functions of flow-based and autoregressive models