📗 Enter your ID here: and click 1,2,3,4,5
📗 The same ID should generate the same set of parameters. Your answers are not saved when you close the browser. You could either copy and paste your console output into the text boxes or print your output to text files (.txt) and load them using the button above the text boxes.
📗 Please report any bugs on Piazza.
📗 (Introduction) You can use any dataset you prefer. You have to implement at least one machine learning or search algorithm from the list below. This homework will be graded manually after the final exam.
📗 The list of algorithms you can build from scratch:
(1) Neural network with more than two hidden layers.
(2) Support vector machines.
(3) Bayesian network.
(4) Gaussian mixture model.
(5) Reinforcement Q-learning.
(6) Minimax with alpha-beta pruning.
📗 The list of algorithms you can build with a machine learning package:
(1) Convolutional neural network.
(2) Recurrent neural network.
(3) Generative adversarial network.
📗 [1 points] Which algorithm did you implement or use? .
📗 [2 points] What dataset did you use or what problem did you solve? .
📗 [3 points] Your implementation is working and produces a reasonable output.
📗 [3 points] You are going to submit a written report (a PDF file) of the results on Canvas.
📗 [5 points] Subjective grade of the quality of the project in comparison to other students' submission.
📗 [5 points] Subjective grade of the difficulty of project in comparison with P1 to P5.
📗 [1 points] You can suggest a grade out of 10 for the previous two parts and provide an explanation (not an essay, please, I will look at your report too).
📗 Grade
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📗 Please copy and paste the text between the *****s (not including the *****s) and submit it on Canvas, P6.
📗 Please submit your code and outputs on Canvas, P6S.
📗 Please submit your report on Canvas, P6S.