Understanding Visual Cortex with Deep Learning Models
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By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Covers the fundamentals of multilayer neural networks and deep learning, including back-propagation and network architectures like LeNet, AlexNet, and VGG-16.
Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.
