fix link

Author: cezannec

weight-initialization/weight_initialization_exercise.ipynb

@@ -102,7 +102,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
@@ -245,7 +247,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "import helpers\n",
@@ -280,7 +284,7 @@
    },
    "source": [
     "### Uniform Distribution\n",
-    "A [uniform distribution](https://en.wikipedia.org/wiki/Uniform_distribution_(continuous%29) has the equal probability of picking any number from a set of numbers. We'll be picking from a continuous distribution, so the chance of picking the same number is low. We'll use NumPy's `np.random.uniform` function to pick random numbers from a uniform distribution.\n",
+    "A [uniform distribution](https://en.wikipedia.org/wiki/Uniform_distribution) has the equal probability of picking any number from a set of numbers. We'll be picking from a continuous distribution, so the chance of picking the same number is low. We'll use NumPy's `np.random.uniform` function to pick random numbers from a uniform distribution.\n",
     "\n",
     ">#### [`np.random_uniform(low=0.0, high=1.0, size=None)`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.uniform.html)\n",
     ">Outputs random values from a uniform distribution.\n",
@@ -297,7 +301,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "helpers.hist_dist('Random Uniform (low=-3, high=3)', np.random.uniform(-3, 3, [1000]))"
@@ -342,7 +348,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# create a new model with these weights\n",
@@ -353,7 +361,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# evaluate behavior \n",
@@ -381,7 +391,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# takes in a module and applies the specified weight initialization\n",
@@ -410,7 +422,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# takes in a module and applies the specified weight initialization\n",
@@ -432,7 +446,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# compare these two models\n",
@@ -471,7 +487,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "helpers.hist_dist('Random Normal (mean=0.0, stddev=1.0)', np.random.normal(size=[1000]))"

weight-initialization/weight_initialization_solution.ipynb

@@ -310,7 +310,7 @@
    },
    "source": [
     "### Uniform Distribution\n",
-    "A [uniform distribution](https://en.wikipedia.org/wiki/Uniform_distribution_(continuous%29) has the equal probability of picking any number from a set of numbers. We'll be picking from a continuous distribution, so the chance of picking the same number is low. We'll use NumPy's `np.random.uniform` function to pick random numbers from a uniform distribution.\n",
+    "A [uniform distribution](https://en.wikipedia.org/wiki/Uniform_distribution) has the equal probability of picking any number from a set of numbers. We'll be picking from a continuous distribution, so the chance of picking the same number is low. We'll use NumPy's `np.random.uniform` function to pick random numbers from a uniform distribution.\n",
     "\n",
     ">#### [`np.random_uniform(low=0.0, high=1.0, size=None)`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.uniform.html)\n",
     ">Outputs random values from a uniform distribution.\n",
@@ -745,7 +745,9 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "model_no_initialization = Net()"