Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.
Explores the mathematics of deep learning, neural networks, and their applications in computer vision tasks, addressing challenges and the need for robustness.
Explores decoding techniques for neural signals using invasive interfaces, regenerative electrodes, and intraneural electrodes to improve prosthesis control and reduce neuroma pain.
Covers the basics of neural networks, activation functions, training, image processing, CNNs, regularization, and dimensionality reduction methods.
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