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  2. Backpropagation - Wikipedia

    en.wikipedia.org/wiki/Backpropagation

    For backpropagation, the activation as well as the derivatives () ′ (evaluated at ) must be cached for use during the backwards pass. The derivative of the loss in terms of the inputs is given by the chain rule; note that each term is a total derivative , evaluated at the value of the network (at each node) on the input x {\displaystyle x} :

  3. Automatic differentiation - Wikipedia

    en.wikipedia.org/wiki/Automatic_differentiation

    Automatic differentiation is a subtle and central tool to automatize the simultaneous computation of the numerical values of arbitrarily complex functions and their derivatives with no need for the symbolic representation of the derivative, only the function rule or an algorithm thereof is required.

  4. Delta rule - Wikipedia

    en.wikipedia.org/wiki/Delta_rule

    To find the right derivative, we again apply the chain rule, this time differentiating with respect to the total input to , : = () Note that the output of the j {\displaystyle j} th neuron, y j {\displaystyle y_{j}} , is just the neuron's activation function g {\displaystyle g} applied to the neuron's input h j {\displaystyle h_{j}} .

  5. Gradient descent - Wikipedia

    en.wikipedia.org/wiki/Gradient_descent

    In the case of gradient descent, that would be when the vector of independent variable adjustments is proportional to the gradient vector of partial derivatives. The gradient descent can take many iterations to compute a local minimum with a required accuracy , if the curvature in different directions is very different for the given function.

  6. Backpropagation through time - Wikipedia

    en.wikipedia.org/wiki/Backpropagation_through_time

    Then, the backpropagation algorithm is used to find the gradient of the loss function with respect to all the network parameters. Consider an example of a neural network that contains a recurrent layer and a feedforward layer . There are different ways to define the training cost, but the aggregated cost is always the average of the costs of ...

  7. Do fish feel pain? Why some scientists are split on the debate

    www.aol.com/news/fish-feel-pain-why-scientists...

    Can fish feel pain? The debate rages among scientists as to whether fish do, in fact, feel pain or are just reacting erratically to certain stimuli.

  8. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    The classical finite-difference approximations for numerical differentiation are ill-conditioned. However, if is a holomorphic function, real-valued on the real line, which can be evaluated at points in the complex plane near , then there are stable methods.

  9. How to Decode the Tiny Stickers on Grocery Store Fruits and ...

    www.aol.com/decode-tiny-stickers-grocery-store...

    GMO labeling and the little-known "8" code. According to the IFPS, there is no mandatory global rule requiring genetically modified produce to be labeled with an “8”; however, some companies ...