Deep Learning - Artificial Neural Networks with Tensorflow - Activation Functions

The video tutorial explores the sigmoid and tanH functions, highlighting their roles in neural networks and their limitations, such as the vanishing gradient problem. It introduces ReLU as a more effective activation function, discussing its advantages and biological plausibility. The tutorial emphasizes the importance of experimentation over theoretical beauty in machine learning.

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