Dexa/Machine Learning Street Talk (MLST)

Neural Network Challenges

Keith discusses the high accuracy demands in engineering compared to neural networks. Tim highlights the complexity of understanding code behavior. Bert emphasizes the need for versatile generative models in active inference for various applications.

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Machine Learning Street Talk (MLST)
Prof. BERT DE VRIES - ON ACTIVE INFERENCE
Related Questions
- How effective are current models in machine learning?
- How do you leverage different models in machine learning as discussed in the episode Domain Adaptation and Generative Models for Single Cell Genomics with Gerald Quon - TWiML Talk #251 and the clip Nested Generative Models?