diff --git a/Ch10-deeplearning-lab.Rmd b/Ch10-deeplearning-lab.Rmd
index c593132..e6911cc 100644
--- a/Ch10-deeplearning-lab.Rmd
+++ b/Ch10-deeplearning-lab.Rmd
@@ -3,12 +3,15 @@ jupyter:
jupytext:
cell_metadata_filter: -all
formats: ipynb,Rmd
- main_language: python
text_representation:
extension: .Rmd
format_name: rmarkdown
format_version: '1.2'
jupytext_version: 1.14.7
+ kernelspec:
+ display_name: Python 3 (ipykernel)
+ language: python
+ name: python3
---
diff --git a/Ch10-deeplearning-lab.ipynb b/Ch10-deeplearning-lab.ipynb
index 0e5c7c1..835512f 100644
--- a/Ch10-deeplearning-lab.ipynb
+++ b/Ch10-deeplearning-lab.ipynb
@@ -897,7 +897,7 @@
{
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+ "model_id": "4cb0d8941d43434883b4142c14e198f8",
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@@ -1569,7 +1569,7 @@
{
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+ "model_id": "840b55ce195b42edbe9f3fd394dec7e5",
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@@ -1583,7 +1583,7 @@
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@@ -1597,7 +1597,7 @@
{
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@@ -1651,7 +1651,7 @@
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@@ -2239,7 +2239,7 @@
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@@ -2766,7 +2766,7 @@
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@@ -2899,7 +2899,7 @@
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@@ -3364,7 +3364,7 @@
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@@ -3860,7 +3860,7 @@
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@@ -4374,7 +4374,7 @@
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- "model_id": "4cf942f623ad4e879dc6ec608fbde15a",
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@@ -4491,7 +4491,7 @@
{
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+ "model_id": "efb32ed16b3946ebbdb7c6a1714c7347",
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@@ -4940,7 +4940,7 @@
{
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- "model_id": "791bef0ec3d54cf29e97d4ad80e97bd6",
+ "model_id": "ae6af1d96e5a4d1fa048bbbf0a3f5b7b",
"version_major": 2,
"version_minor": 0
},
@@ -5548,36 +5548,36 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Image: book_images/flamingo.jpg\n",
+ "Image: book_images/Cape_Weaver.jpg\n",
+ " label prob\n",
+ "0 jacamar 0.298104\n",
+ "1 macaw 0.068012\n",
+ "2 lorikeet 0.051065\n",
+ "Image: book_images/Flamingo.jpg\n",
" label prob\n",
"0 flamingo 0.606624\n",
"1 spoonbill 0.013324\n",
"2 American_egret 0.002130\n",
- "Image: book_images/hawk.jpg\n",
+ "Image: book_images/Hawk_Fountain.jpg\n",
" label prob\n",
"0 kite 0.187797\n",
"1 robin 0.084580\n",
"2 great_grey_owl 0.059789\n",
- "Image: book_images/hawk_cropped.jpeg\n",
+ "Image: book_images/Hawk_cropped.jpg\n",
" label prob\n",
"0 kite 0.454471\n",
"1 great_grey_owl 0.015789\n",
"2 jay 0.011916\n",
- "Image: book_images/huey.jpg\n",
+ "Image: book_images/Lhasa_Apso.jpg\n",
" label prob\n",
"0 Lhasa 0.260186\n",
"1 Shih-Tzu 0.097995\n",
"2 Tibetan_terrier 0.032107\n",
- "Image: book_images/kitty.jpg\n",
+ "Image: book_images/Sleeping_Cat.jpg\n",
" label prob\n",
"0 Persian_cat 0.163612\n",
"1 tabby 0.074585\n",
- "2 tiger_cat 0.042531\n",
- "Image: book_images/weaver.jpg\n",
- " label prob\n",
- "0 jacamar 0.298104\n",
- "1 macaw 0.068012\n",
- "2 lorikeet 0.051065\n"
+ "2 tiger_cat 0.042531\n"
]
}
],
@@ -5925,7 +5925,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "35472ab593724d8c968c028c98e2d75d",
+ "model_id": "57e25e1e102745c18849507d8fe93fe3",
"version_major": 2,
"version_minor": 0
},
@@ -6393,7 +6393,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "20a1f379f4de4cbe945350e2e4b76229",
+ "model_id": "57a8b619aaf049b4b06550a47d5e3611",
"version_major": 2,
"version_minor": 0
},
@@ -6896,7 +6896,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "49633d08494c494a927bdb51c577d2b1",
+ "model_id": "4abe857cc251478b8855f53164fa5b45",
"version_major": 2,
"version_minor": 0
},
@@ -7222,7 +7222,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "a0beddf501d94f32b24c41687ee61907",
+ "model_id": "1648bfd17bc04050b412c36afb32e092",
"version_major": 2,
"version_minor": 0
},
@@ -7240,8 +7240,8 @@
"┃ Runningstage.testing ┃ ┃\n",
"┃ metric ┃ DataLoader 0 ┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
- "│ test_accuracy │ 0.8569200038909912 │\n",
- "│ test_loss │ 0.8614107370376587 │\n",
+ "│ test_accuracy │ 0.8388800024986267 │\n",
+ "│ test_loss │ 0.8145671486854553 │\n",
"└───────────────────────────┴───────────────────────────┘\n",
"\n"
],
@@ -7250,8 +7250,8 @@
"┃\u001b[1m \u001b[0m\u001b[1m Runningstage.testing \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m┃\n",
"┃\u001b[1m \u001b[0m\u001b[1m metric \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m DataLoader 0 \u001b[0m\u001b[1m \u001b[0m┃\n",
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
- "│\u001b[36m \u001b[0m\u001b[36m test_accuracy \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m 0.8569200038909912 \u001b[0m\u001b[35m \u001b[0m│\n",
- "│\u001b[36m \u001b[0m\u001b[36m test_loss \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m 0.8614107370376587 \u001b[0m\u001b[35m \u001b[0m│\n",
+ "│\u001b[36m \u001b[0m\u001b[36m test_accuracy \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m 0.8388800024986267 \u001b[0m\u001b[35m \u001b[0m│\n",
+ "│\u001b[36m \u001b[0m\u001b[36m test_loss \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m 0.8145671486854553 \u001b[0m\u001b[35m \u001b[0m│\n",
"└───────────────────────────┴───────────────────────────┘\n"
]
},
@@ -7261,7 +7261,7 @@
{
"data": {
"text/plain": [
- "[{'test_loss': 0.8614107370376587, 'test_accuracy': 0.8569200038909912}]"
+ "[{'test_loss': 0.8145671486854553, 'test_accuracy': 0.8388800024986267}]"
]
},
"execution_count": 91,
@@ -7301,7 +7301,7 @@
},
{
"data": {
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",
+ "image/png": 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