minor polish

Author: amueller

01 - Why scikit-learn.ipynb

@@ -25,24 +25,6 @@
     "* Provides \"standard\" bits of your ML worflow.\n",
     "* Tooling in which you can plug in your custom model with ease."
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "collapsed": true
-   },
-   "source": [
-    "#scikit-learn.github.io/dev"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

02 - First Steps.ipynb

@@ -411,6 +411,19 @@
     "Then train an evaluate a classifier of your choice.\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.datasets import load_iris\n",
+    "iris = load_iris()\n",
+    "print(iris.DESCR)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

06 - Grid Searches for Hyper Parameters.ipynb

@@ -158,8 +158,6 @@
    "outputs": [],
    "source": [
     "# We extract just the scores\n",
-    "%matplotlib inline\n",
-    "import matplotlib.pyplot as plt\n",
     "\n",
     "scores = [x.mean_validation_score for x in grid_search.grid_scores_]\n",
     "scores = np.array(scores).reshape(6, 5)\n",

08 - Working With Text Data.ipynb

@@ -13,6 +13,13 @@
     "import numpy as np"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Working with Text Data"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -310,7 +317,7 @@
     "* Create a pipeine using the count vectorizer and SVM (see 07). Train and score using the pipeline.\n",
     "* Vary the n_gram_range in the count vectorizer, visualize the changed coefficients.\n",
     "* Grid search the C in the LinearSVC using the pipeline.\n",
-    "* Grid search the C in the LinearSVC together with the n_gram_range."
+    "* Grid search the C in the LinearSVC together with the n_gram_range (try (1,1), (1, 2), (2, 2))"
    ]
   },
   {