| 6과목 1장 |
내용출처 |
286-288 |
7-1) CNN case study - LeNet-5 |
-
|
https://www.youtube.com/watch?v=EPFQ3z2xIQ8
|
| 6과목 1장 |
내용출처 |
291 |
7-3) CNN case study - ResNet |
-
|
https://www.youtube.com/watch?v=1PGLj-uKT1w
|
| 6과목 1장 |
내용출처 |
294 |
8-2) CNN for CT images |
-
|
https://www.slideshare.net/GYLee3/ss-72966495
|
| 6과목 1장 |
코드 |
294-298 |
8) CNN Basics |
[6과목1장] 8. CNN Basics.ipynb
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/lab-11-0-cnn_basics.ipynb
|
| 6과목 1장 |
내용출처 |
298 |
9-1) Simple CNN |
-
|
http://personal.ie.cuhk.edu.hk/~ccloy/project_target_code/index.html
|
| 6과목 1장 |
코드 |
298-300 |
9) MNIST 99% with CNN (1-6) |
[6과목1장] 9. MNIST 99% with CNN (1-6).ipynb
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/pytorch/lab-11-1-mnist_cnn.py
|
| 6과목 1장 |
코드 |
301-302 |
9-7) Deep CNN |
-
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/pytorch/lab-11-2-mnist_deep_cnn.py
|
| 6과목 2장 |
내용출처 |
318 |
4-1) RNN applications |
-
|
https://github.com/TensorFlowKR/awesome_tensorflow_implementations
|
| 6과목 2장 |
코드 |
321-322 |
6) RNN Basics (2) |
[6과목2장] 6-2. one node 5 (input-dim) in 2 (hidden_size).ipynb
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/lab-12-0-rnn_basics.ipynb
|
| 6과목 2장 |
코드 |
322-323 |
6) RNN Basics (3) |
[6과목2장] 6-3. Upfolding to n sequences.ipynb
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/lab-12-0-rnn_basics.ipynb
|
| 6과목 2장 |
코드 |
323-324 |
6) RNN Basics (4) |
[6과목2장] 6-4. Batching input.ipynb
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/lab-12-0-rnn_basics.ipynb
|
| 6과목 2장 |
코드 |
324-328 |
7) Teach RNN |
[6과목2장] 7. Teach RNN.ipynb
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/lab-12-1-hello-rnn.py
|
| 6과목 2장 |
코드 |
328-329 |
8) RNN with long sequences |
[6과목2장] 8. RNN with long sequences.ipynb
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/lab-12-2-char-seq-rnn.py
|
| 6과목 2장 |
코드 |
331-335 |
9) RNN with long sequences With Fully Connection layer |
[6과목2장] 9. RNN with long sequences With Fully Connection layer.ipynb
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/lab-12-4-rnn_long_char.py
|
| 6과목 2장 |
코드 |
335-336 |
10) RNN with long sequences : Stacked RNN |
[6과목2장] 10. RNN with long sequences (Stacked RNN).ipynb
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/lab-12-4-rnn_long_char.py
|
| 6과목 2장 |
코드 |
337 |
10-5) chr/word rnn (char/word level n to n model) |
-
|
https://github.com/sherjilozair/char-rnn-tensorflow
|
| 6과목 2장 |
코드 |
337 |
10-5) chr/word rnn (char/word level n to n model) |
-
|
https://github.com/hunkim/word-rnn-tensorflow
|
| 6과목 2장 |
코드 |
337-338 |
11) RNN with long sequences : Dynamic RNN |
[6과목2장] 11. RNN with long sequences (Dynamic RNN).ipynb
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/lab-12-0-rnn_basics.ipynb
|
| 6과목 2장 |
코드 |
339-341 |
12) RNN with time series data(stock) |
[6과목2장] 12. RNN with time series data(stock).ipynb
|
https://github.com/hunkim/DeepLearningZeroToAll/blob/master/lab-12-5-rnn_stock_prediction.py
|
| 6과목 2장 |
데이터 |
339 |
12) RNN with time series data(stock) |
amazon.csv
|
-
|