Questions tagged [backpropagation]

Backpropagation is a method of the gradient computation, often used in artificial neural networks to perform gradient descent.

Backpropagation is a method of the gradient computation, often used in artificial neural networks to perform gradient descent. It led to a “renaissance” in the field of artificial neural network research.

In most cases, it requires a teacher that knows, or can calculate, the desired output for any input in the training set. The term is an abbreviation for "backward propagation of errors".

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How to calculate gradient descent cost for the weights using a dot product?

I'm trying to reproduce a neural network from http://neuralnetworksanddeeplearning.com/chap2.html What i don't get is why they can calculate the gradient descent for the weights by taking a dot product of the error/delta and the transposed…

asked Dec 29 '18 at 14:30

Sivan Duijn

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Why do we have to backpropagate error before applying gradient descent?

When I looked at these notes: I was confused about the 4th step. Why should we calculate the errors separately when the gradient descent already computes it. So, would not we be computing the backpropagation error twice? Thanks

machine-learning neural-network backpropagation

asked Feb 10 '18 at 12:15

Huzo

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How to initialize an array of structs with another stuct?

Hello I am writing an algorithm for back propagation in c++, it consists of 1 input layer 1 hidden layer and 1 output layer. I am curious how to initialize my inputlayer, hiddenlayer, and outputlayer. This is what i got: struct Neuron { double…

c++ machine-learning backpropagation

asked Apr 14 '13 at 19:01

jamalsabs

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What is the best way to normalize negative/non numerical data for tanh activation function neural networks

I'm using feed forward, gradient descent, backpropagation neural networks where hidden/output neurons are using tanh activation function and input neurons are linear. What is the best way, in your opinion, for normalizing numerical data if: Maximum…

c++ machine-learning neural-network artificial-intelligence backpropagation

asked Apr 12 '16 at 17:39

Gyiove Sparkle

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How do you train a neural network without an exact answer?

Most neural networks use backpropagation to learn, but from how I've understood it you need an exact answer to what the outputs should be for this to work. What I want to do is to learn a walker bot to walk, and have a score or fitness variable to…

python neural-network deep-learning keras backpropagation

asked Mar 23 '18 at 12:23

Rasmus Anker Fossen Nordal

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2 answers

Data Encoding for Training in Neural Network

I have converted 349,900 words from a dictionary file to md5 hash. Sample are…

machine-learning encoding neural-network backpropagation perceptron

asked Oct 25 '18 at 06:31

alyssaeliyah

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