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Explore neural network training fundamentals in this 77-minute lecture covering blood-brain barrier (BBB) transmission prediction modeling. Learn essential concepts starting with model creation for BBB transmission, followed by comprehensive coverage of neural network training principles including momentum methods and simple linear model fitting. Dive into crucial concepts like bias/variance tradeoff and various regularization techniques. Master advanced optimization approaches with Adam optimizer and L2 penalty implementation, while understanding the importance of batch normalization in deep learning. Conclude by applying these concepts to practical model development, with access to detailed lecture notes, slides, and supplementary materials for deeper understanding.
Training Neural Networks and Deep Learning Optimization Methods - Lecture 16