Advanced Generative Models
Understand and utilize advanced generative models for AI applications.
Learning Objectives
Implement and optimize generative models for complex tasks.
Topics
Variational Autoencoders
Explore VAEs and their use in probabilistic modeling.
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Generative Adversarial Networks
Study GANs and their applications in generating realistic data.
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Flow-based Models
Understand flow-based models and their applications in density estimation.
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Energy-based Models
Study energy-based models and their applications in AI.
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Diffusion Models
Learn about diffusion models for generating high-quality data.
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Score-Based Generative Models
Examine score-based models and their role in generative modeling.
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Autoregressive Models
Understand autoregressive models for sequential data generation.
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Model Evaluation and Tuning
Master techniques for evaluating and tuning generative models.
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Realtime audio conversation for interactive session.
Interactive realtime chat session.
Live whiteboard explanation and collaboration.
Real-time wide variety of examples.
Continuous assessment and feedback.
Progress monitoring and record progress journey.
Broadcast session with larger audience for free.
Attend audience queries and provide responses.