arthur/handson-ml3
1
0
Fork 0
mirror of https://github.com/ArthurDanjou/handson-ml3.git synced 2026-01-14 12:14:36 +01:00
Code Issues Packages Projects Releases Wiki Activity

Update libraries to latest version, including TensorFlow 2.4.1 and Scikit-Learn 0.24.1

Browse Source
This commit is contained in:
Aurélien Geron
2021-02-14 15:02:09 +13:00
parent 8ebdcffc6b
commit 670873843d
15 changed files with 797 additions and 737 deletions
Download Patch File Download Diff File Expand all files Collapse all files

16
13_loading_and_preprocessing_data.ipynb
View File

@@ -1026,7 +1026,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"**Warning**: there's currently a bug preventing `from tensorflow.train import X` so we work around it by writing `X = tf.train.X`. See https://github.com/tensorflow/tensorflow/issues/33289 for more details."
"**Warning**: in TensorFlow 2.0 and 2.1, there was a bug preventing `from tensorflow.train import X` so we work around it by writing `X = tf.train.X`. See https://github.com/tensorflow/tensorflow/issues/33289 for more details."
]
},
{
@@ -1294,7 +1294,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"**Warning**: there's currently a bug preventing `from tensorflow.train import X` so we work around it by writing `X = tf.train.X`. See https://github.com/tensorflow/tensorflow/issues/33289 for more details."
"**Warning**: in TensorFlow 2.0 and 2.1, there was a bug preventing `from tensorflow.train import X` so we work around it by writing `X = tf.train.X`. See https://github.com/tensorflow/tensorflow/issues/33289 for more details."
]
},
{
@@ -1430,7 +1430,7 @@
"source": [
"import os\n",
"import tarfile\n",
"import urllib\n",
"import urllib.request\n",
"\n",
"DOWNLOAD_ROOT = \"https://raw.githubusercontent.com/ageron/handson-ml2/master/\"\n",
"HOUSING_PATH = os.path.join(\"datasets\", \"housing\")\n",
@@ -2120,7 +2120,7 @@
},
{
"cell_type": "code",
"execution_count": 162,
"execution_count": 130,
"metadata": {},
"outputs": [],
"source": [
@@ -2267,7 +2267,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"It takes about 20 seconds to load the dataset and go through it 10 times."
"It takes about 17 seconds to load the dataset and go through it 10 times."
]
},
{
@@ -2306,7 +2306,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Now it takes about 34 seconds to go through the dataset 10 times. That's much slower, essentially because the dataset is not cached in RAM, so it must be reloaded at each epoch. If you add `.cache()` just before `.repeat(10)`, you will see that this implementation will be about as fast as the previous one."
"Now it takes about 33 seconds to go through the dataset 10 times. That's much slower, essentially because the dataset is not cached in RAM, so it must be reloaded at each epoch. If you add `.cache()` just before `.repeat(10)`, you will see that this implementation will be about as fast as the previous one."
]
},
{
@@ -2609,7 +2609,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"We get about 75% accuracy on the validation set after just the first epoch, but after that the model makes no progress. We will do better in Chapter 16. For now the point is just to perform efficient preprocessing using `tf.data` and Keras preprocessing layers."
"We get about 73.7% accuracy on the validation set after just the first epoch, but after that the model makes no significant progress. We will do better in Chapter 16. For now the point is just to perform efficient preprocessing using `tf.data` and Keras preprocessing layers."
]
},
{
@@ -2766,7 +2766,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
"version": "3.7.9"
},
"nav_menu": {
"height": "264px",