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Write a python program based on the discussion we had on the last day of class, to train a network with two hidden layers each with 5 neurons. Finish the gradient computation we did in class, and implement a steepest decent search for a network which minimizes the cost function. Once you believe that your network is trained, compute the value of n(1, 1) and see what you get. Bonus: If you easily get this to work, then try to generalize to K neurons in each of the two hidden layers. Does the training work better with more neurons

Write a python program based on the discussion we had on the last day of class, to train a network with two hidden layers each with 5 neurons. Finish the gradient computation we did in class, and implement a steepest decent search for a network which minimizes the cost function. Once you believe that your network is trained, compute the value of n(1, 1) and see what you get. Bonus: If you easily get this to work, then try to generalize to K neurons in each of the two hidden layers. Does the training work better with more neurons

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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Write a python program based on the discussion we had on the last day of class, to train a network with two hidden layers each with 5 neurons. Finish the gradient computation we did in class, and implement a steepest decent search for a network which minimizes the cost function. Once you believe that your network is trained, compute the value of n(1, 1) and see what you get. Bonus: If you easily get this to work, then try to generalize to K neurons in each of the two hidden layers. Does the training work better with more neurons? 

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