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Results tagged with gradient-descent
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user 24077
Gradient Descent is an algorithm for finding the minimum of a function. It iteratively calculates partial derivatives (gradients) of the function and descends in steps proportional to those partial derivatives. One major application of Gradient Descent is fitting a parameterized model to a set of data: the function to be minimized is an error function for the model.
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Does the performance of neural networks depend on the method used to unroll weights ?
Lets say we have weights(theta1 and theta2) of neural net as:
theta1 =[1, 2, 3]
theta2= [4, 5, 6]
If we unroll these weights into a single dimension array in matlab/octave ,we get:
theta = [theta1 …
- 227
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Can overfitting occur in Advanced Optimization algorithms?
while taking an online course on machine learning by Andrew Ng on coursera, I came across a topic called overfitting. I know it can occur when gradient descent is used in linear or logistic regression …
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