* Design a neural network that has two input nodes x1, x2 and one output node y. The to-be-learned function is y= x1 * x2. You can assume that 0 <= x1, x2 <= 1. 2.1 ( be? 2.2 pu, Describe your network structure. How many layers : 2, how many nodes in each layer and how nodes are connected. 2.3 ( What is your activation function? How do you obtain your training/validation/test set? How large will each sets

Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
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Design a neural network that has two input nodes x1, x2 and one
outpút node y. The to-be-learned function is y= x1 * x2. You can assume
that 0 <= x1, x2 <= 1.
2.1(
be?
How do you obtain your training/validation/test set? How large will each sets
Describe your network structure. How many layers : 2, how many nodes in
2.2
each layer and how nodes are connected.
2.3 ( : What is your activation function?
2.4 (
Describe your loss function
„How do you update your weights and biases?
Show your trained weights/biases
2.5
2.6 (*
2.
Transcribed Image Text:Design a neural network that has two input nodes x1, x2 and one outpút node y. The to-be-learned function is y= x1 * x2. You can assume that 0 <= x1, x2 <= 1. 2.1( be? How do you obtain your training/validation/test set? How large will each sets Describe your network structure. How many layers : 2, how many nodes in 2.2 each layer and how nodes are connected. 2.3 ( : What is your activation function? 2.4 ( Describe your loss function „How do you update your weights and biases? Show your trained weights/biases 2.5 2.6 (* 2.
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