2020/11/25 COMP9444 Exercises 3 COMP9444 Neural Networks and Deep Learning Term 3, 2020 Exercises 3: Probability This page was last updated: 09/30/2020 07:15:12 1. Bayes’ Rule One bag contains 2 red balls and 3 white balls. Another bag contains 3 red balls and 2 green balls. One of these bags is chosen at random, and […]
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COMP9444 Neural Networks and Deep Learning COMP9444 ⃝c Alan Blair, 2017-20 10a. Review COMP9444 20T3 Review 1 Assessment Assessment will consist of: Assignment 1 30% Assignment 2 30% Final Exam 40% The Final Exam will be available on Moodle. You will have 2 hours to complete the exam, within the window of 14:00 to 17:00
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2020/11/25 COMP9444 Exercises 2 COMP9444 Neural Networks and Deep Learning Term 3, 2020 Exercises 2: Backpropagation This page was last updated: 09/30/2020 07:13:44 1. Identical Inputs Consider a degenerate case where the training set consists of just a single input, repeated 100 times. In 80 of the 100 cases, the target output value is 1;
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2020/11/25 COMP9444 Exercises 5 COMP9444 Neural Networks and Deep Learning Term 3, 2020 Exercises 6: Word Vectors This page was last updated: 11/08/2020 06:09:01 1. Consider the sentence “two flowers grew tall on two tall towers” a. Write the co-occurrence matrix X for this sentence, using a 4-word context window (i.e. two context words on
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2020/11/25 COMP9444 Exercises 6 COMP9444 Neural Networks and Deep Learning Term 3, 2020 Exercises 7: Reinforcement Learning This page was last updated: 11/08/2020 06:07:55 Consider an environment with two states S = {S1, S2} and two actions A = {a1, a2}, where the (deterministic) transitions ¦Ä and reward R for each state and action are
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2020/11/25 COMP9444 Exercises 5 COMP9444 Neural Networks and Deep Learning Term 3, 2020 Exercises 5: Hidden Units and Convolution This page was last updated: 10/26/2020 11:19:48 1. Hidden Unit Dynamics Consider a fully connected feedforward neural network with 6 inputs, 2 hidden units and 3 outputs, using tanh activation at the hidden units and sigmoid
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2020/11/25 COMP9444 Exercises 4 COMP9444 Neural Networks and Deep Learning Term 3, 2020 Exercises 4: PyTorch This page was last updated: 10/09/2020 11:24:33 Download the zip file Ex4code.zip and unzip it. This will create a directory Ex4code with two very simple PyTorch programs, slope.py and xor.py. 1. Adjusting the Learning Rate and Momentum The program
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COMP9444 Neural Networks and Deep Learning Outline COMP9444 ⃝c Alan Blair, 2017-20 COMP9444 ⃝c Alan Blair, 2017-20 COMP9444 20T3 Word Vectors 2 COMP9444 20T3 Word Vectors 3 What is the meaning of meaning? stylish, graceful, tasteful, discerning, refined, sophisticated, dignified, cultivated, distinguished, classic, smart, fashionable, modish, decorous, beautiful, artistic, aesthetic, lovely; charming, polished, suave, urbane,
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2020/11/25 COMP9444 Exercises 8 COMP9444 Neural Networks and Deep Learning Term 3, 2020 Exercises 8: Hopfield Networks This page was last updated: 11/08/2020 06:09:19 1. a. Compute the weight matrix for a Hopfield network with the two memory vectors [1, –1, 1, –1, 1, 1] and [1, 1, 1, –1, –1, –1] stored in it.
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COMP9444 Neural Networks and Deep Learning Outline 9b. Generative Adversarial Networks Artist-Critic Co-Evolution Co-Evolution Paradigms Blind Watchmaker (GP Artist, Human Critic) Evolutonary Art (GP Artist, GP or NN Critic) Generative Adversarial Networks (CNN Artist, CNN Critic) COMP9444 ⃝c Alan Blair, 2017-20 COMP9444 ⃝c Alan Blair, 2017-20 COMP9444 20T3 Generative Adversarial
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