Activation Functions - EXPLAINED!
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We start with the whats/whys/hows. Then delve into details (math) with examples. Follow me on M E D I U M: https://towardsdatascience.com/likelihood-probability-and-the-math-you-should-know-9bf66db5241b REFERENCES [1] Amazing discussion on the "dying relu problem": https://www.quora.com/What-is-the-dying-ReLU-problem-in-neural-networks [2 ...
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Activation Function Explained
Algorithms | CS | Data Science on Instagram: "A Feedforward Neural Network (or Multi-Layer Perceptron - MLP) is a pure mathematical pipeline! Neurons are stacked in layers, and each one executes a precise calculation: it takes the inputs from the prior layer, subjects them to its internal weights, adds a bias, and then funnels the sum through an activation function to produce an output. This process streams forward, layer by layer, until the network delivers its final prediction. The network imm
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Algorithms | CS | Data Science on Instagram: "A Feedforward Neural Network (or Multi-Layer Perceptron - MLP) is a pure mathematical pipeline! Neurons are stacked in layers, and each one executes a precise calculation: it takes the inputs from the prior layer, subjects them to its internal weights, adds a bias, and then funnels the sum through an activation function to produce an output. This process streams forward, layer by layer, until the network delivers its final prediction. The network imm
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