Respond to the question with a concise and accurate answer, along with a clear explanation and step-by-step solution, or risk receiving a downvote. 1-What is the difference between neural networks and softmax. 2-discuss the right amount learning rate and its effect on the gradient descent algorithm. 3-What is the difference between sum of square error see , sigmoid and soft max in terms of the effect of noise Outlier. 4-List the advantages and disadvantages of advanced optimization methods

Respond to the question with a concise and accurate answer, along with a clear explanation and step-by-step solution, or risk receiving a downvote. 1-What is the difference between neural networks and softmax. 2-discuss the right amount learning rate and its effect on the gradient descent algorithm. 3-What is the difference between sum of square error see , sigmoid and soft max in terms of the effect of noise Outlier. 4-List the advantages and disadvantages of advanced optimization methods

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Respond to the question with a concise and accurate answer, along with a clear explanation and step-by-step solution, or risk receiving a downvote.

1-What is the difference between neural networks and softmax.

2-discuss the right amount learning rate and its effect on the gradient descent algorithm.

3-What is the difference between sum of square error see , sigmoid and soft max in terms of the effect of noise Outlier.

4-List the advantages and disadvantages of advanced optimization methods

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