From a2ce92dcdcce2060540ac1979a05d470197f7c07 Mon Sep 17 00:00:00 2001
From: Mikolaj Rybinski <mikolaj.rybinski@id.ethz.ch>
Date: Mon, 25 Feb 2019 14:50:32 +0100
Subject: [PATCH] index notebook + cleanup TODOs
---
01_introduction.ipynb | 30 +++++++++---------
02_classification.ipynb | 29 +++++++++---------
index.ipynb | 67 +++++++++++++++++++++++++++++++++++++++++
3 files changed, 96 insertions(+), 30 deletions(-)
create mode 100644 index.ipynb
diff --git a/01_introduction.ipynb b/01_introduction.ipynb
index ad2a704..4646eba 100644
--- a/01_introduction.ipynb
+++ b/01_introduction.ipynb
@@ -615,7 +615,7 @@
"\n",
"Examples of supervised learning:\n",
"\n",
- "- Classification: predict the class `is_yummy` based on the attributes `alcohol_content`,\t`bitterness`, \t`darkness` and `fruitiness` (a standard two class problem).\n",
+ "- Classification: predict the class `is_yummy` based on the attributes `alcohol_content`,\t`bitterness`, \t`darkness` and `fruitiness` (a standard two-class problem).\n",
"\n",
"- Classification: predict the digit-shown based on a 8 x 8 pixel image (a multi-class problem).\n",
"\n",
@@ -696,7 +696,7 @@
"metadata": {},
"source": [
"<div class=\"alert alert-block alert-danger\">\n",
- "<strong>TODO:</strong> transform to a set of small exercises (instead of a tutorial/example as it is now).\n",
+ "<strong>TODO:</strong> hands-on or exercise? If latter, then transform to a set of small exercises and mark solutions cells w/ <code>#SOLUTION</code> first line.\n",
"</div>\n",
"\n"
]
@@ -1290,15 +1290,6 @@
"# Exercise section 1"
]
},
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "<div class=\"alert alert-block alert-danger\">\n",
- "<strong>TODO:</strong> I propose to start separate excercise session 2 w/ SVC here (so if someone is stuck on previous, he/she can skip).\n",
- "</div>"
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
@@ -1318,6 +1309,17 @@
"</div>"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from sklearn.svm import SVC\n",
+ "classifier = SVC()\n",
+ "# ..."
+ ]
+ },
{
"cell_type": "code",
"execution_count": 19,
@@ -1333,9 +1335,7 @@
}
],
"source": [
- "from sklearn.svm import SVC\n",
- "# ...\n",
- "# REMOVE or HIDE the following lines in the target script\n",
+ "#SOLUTION\n",
"classifier = SVC()\n",
"classifier.fit(input_features, labels)\n",
"\n",
@@ -1985,7 +1985,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.6"
+ "version": "3.7.2"
}
},
"nbformat": 4,
diff --git a/02_classification.ipynb b/02_classification.ipynb
index 1683c6d..368e108 100644
--- a/02_classification.ipynb
+++ b/02_classification.ipynb
@@ -326,18 +326,6 @@
"In `scikit-learn` the weights of a trained linear classifier are availble via the `coef_` attribute. Extract the weights from the `LogisticRegression` classifier example from the last script and try them out in your weighted sum scoring function."
]
},
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Solution\n",
- "<div class=\"alert alert-block alert-danger\">\n",
- "<strong>TODO:</strong> keep only in \"solutions\" script variant.\n",
- "\n",
- "TODO: write script which removes the solution proposals and creates a new notebook.\n",
- "</div>\n"
- ]
- },
{
"cell_type": "code",
"execution_count": 6,
@@ -408,7 +396,7 @@
}
],
"source": [
- "# TODO: move to solutions script\n",
+ "#SOLUTION\n",
"from sklearn.linear_model import LogisticRegression\n",
"classifier = LogisticRegression()\n",
"input_features = beer_data.iloc[:, :-1]\n",
@@ -694,7 +682,9 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "**TODO: maybe remove the plot, better: animated gif**"
+ "<div class=\"alert alert-block alert-danger\"><p>\n",
+ " <strong>TODO</strong>: remove the plot or, better, insert animated gif w/ bettter surface image than wireframe\n",
+ "</p></div>"
]
},
{
@@ -1278,6 +1268,15 @@
"## Exercise section 2"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "<div class=\"alert alert-block alert-danger\"><p>\n",
+ " <strong>TODO</strong>: split into smaller steps and solutions, rm tuning of classifiers parameters if not necessary (they won't know what it does).\n",
+ "</p></div>"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
@@ -1829,7 +1828,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.6"
+ "version": "3.7.2"
}
},
"nbformat": 4,
diff --git a/index.ipynb b/index.ipynb
new file mode 100644
index 0000000..eeab403
--- /dev/null
+++ b/index.ipynb
@@ -0,0 +1,67 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "<div class=\"alert alert-block alert-danger\">\n",
+ "Course layout w/ local notebooks links .. anything in scope of org/general comments goes also here.\n",
+ "</div>\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "<div class=\"alert alert-block alert-danger\"><p>\n",
+ "<strong>TODOs</strong>\n",
+ "<ol>\n",
+ "<li>Write script which removes the solution proposals (cells starting with <code>#SOLUTION</code>) and creates a new notebook.</li>\n",
+ "</ol>\n",
+ "</p></div>\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Course scripts\n",
+ "\n",
+ "<ol>\n",
+ " <li><a href=\"01_introduction.ipynb\">Introduction</a></li>\n",
+ " <li><a href=\"02_classification.ipynb\">Classification</a></li>\n",
+ " <li>...</li>\n",
+ " \n",
+ "</ol>"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.2"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
--
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