2020 기초인공지능 플젝2
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"2020 기초인공지능 플젝2"에 대한 내용입니다.
목차
1. Question 1: AlexNet with CIFAR-10
2. Question 2: Transfer Learning
본문내용
PyTorch was used, on Google Colab (https://colab.research.google.com/ (https://colab.research.google.com/))
Because of the code size, there are two sections!!
Please follow the page marked at the bottom of the paper.
Question 1: Section 1 - Starts from page 1
Page 12: Question 1 - (b)
Page 13: Question 1 - (c), (d)
Question 2: Section 2 - Starts from page 24
Page 3: Question 2 - (a)
Page 9: Question 2 - (b), (c)
Page 10: Appendix - Code for each model
Question 1: AlexNet with CIFAR-10
(a) Describe training setup e.g. data pre-processing/augmentation, initialization, hyperparameters such
as learning rate schedule, momentum, dropout rate, batch number, BN etc. Present them systematically
in the table form.
The tables below shows the summarized specification of this design. First, the optimal methods used for this
model found has the condition of:
Pre-processing Augmentation LR Scheduler Optimizer
Z-score
normalization
RandomCrop,
RandomHorizontalFlip,
ColorJitter,
RandomGrayscale
참고 자료
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