random seed and typos

Author: Ragav Venkatesan

workshop/lec1/dataset.py

@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
+np.random.seed(42)
 
 class dataset_generator(object):
     """ 

workshop/lec1/lec1.ipynb

@@ -28,7 +28,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from dataset import dataset_generator\n",
@@ -83,7 +85,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from analytical_solution import regressor\n",
@@ -103,7 +107,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from errors import rmse\n",
@@ -122,7 +128,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "r.plot(data_train)"
@@ -134,13 +142,6 @@
    "source": [
     "We can clearly see here that our simple model works pretty fine. Although for this simple linear model an analytical solution does exist, we find that for more complex problem structures we have to rely on some optimization procedures that are described in the later lectures."
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "This notebook was written by Ragav Venkatesan ([email protected]) with material referred from the book 'Convolutional Neural Networks in Visual Computing'. Some of the material might be copyrighted to the author and other copyright holders."
-   ]
   }
  ],
  "metadata": {