update from upstream

.gitignore

@@ -10,5 +10,3 @@ my_*
 datasets/words
 datasets/flowers
 datasets/spam
-*.gz
-datasets/mnist/train-labels-idx1-ubyte

environment.yml

@@ -1,16 +0,0 @@
-name: handson-ml
-dependencies:
-- python=3.5
-- jupyter
-- matplotlib
-- numexpr
-- numpy
-- pandas
-- Pillow
-- psutil
-- scikit-learn
-- scipy
-- sympy
-- pip:
-  - tensorflow
-  - watermark

extra_capsnets.ipynb

@@ -607,7 +607,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Okay, let's start by creating a trainable variable of shape (1, 1152, 10, 16, 8) that will hold all the transformation matrices. The first dimension of size 1 will make this array easy to tile. We initialize this variable randomly using a normal distribution with a standard deviation to 0.01."
+    "Okay, let's start by creating a trainable variable of shape (1, 1152, 10, 16, 8) that will hold all the transformation matrices. The first dimension of size 1 will make this array easy to tile. We initialize this variable randomly using a normal distribution with a standard deviation to 0.1."
    ]
   },
   {
@@ -616,7 +616,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "init_sigma = 0.01\n",
+    "init_sigma = 0.1\n",
     "\n",
     "W_init = tf.random_normal(\n",
     "    shape=(1, caps1_n_caps, caps2_n_caps, caps2_n_dims, caps1_n_dims),\n",