diff --git a/recursion_dynamic/knapsack_unbounded/__init__.py b/recursion_dynamic/knapsack_unbounded/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/recursion_dynamic/knapsack_unbounded/knapsack_unbounded_challenge.ipynb b/recursion_dynamic/knapsack_unbounded/knapsack_unbounded_challenge.ipynb
new file mode 100644
index 0000000..b651724
--- /dev/null
+++ b/recursion_dynamic/knapsack_unbounded/knapsack_unbounded_challenge.ipynb
@@ -0,0 +1,211 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "This notebook was prepared by [Donne Martin](https://github.com/donnemartin). Source and license info is on [GitHub](https://github.com/donnemartin/interactive-coding-challenges)."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Challenge Notebook"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Problem: Given a knapsack with a total weight capacity and a list of items with weight w(i) and value v(i), determine the max total value you can carry.\n",
+ "\n",
+ "* [Constraints](#Constraints)\n",
+ "* [Test Cases](#Test-Cases)\n",
+ "* [Algorithm](#Algorithm)\n",
+ "* [Code](#Code)\n",
+ "* [Unit Test](#Unit-Test)\n",
+ "* [Solution Notebook](#Solution-Notebook)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Constraints\n",
+ "\n",
+ "* Can we replace the items once they are placed in the knapsack?\n",
+ " * Yes, this is the unbounded knapsack problem\n",
+ "* Can we split an item?\n",
+ " * No\n",
+ "* Can we get an input item with weight of 0 or value of 0?\n",
+ " * No\n",
+ "* Do we need to return the items that make up the max total value?\n",
+ " * No, just the total value\n",
+ "* Can we assume the inputs are valid?\n",
+ " * No\n",
+ "* Are the inputs in sorted order by val/weight?\n",
+ " * Yes\n",
+ "* Can we assume this fits memory?\n",
+ " * Yes"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Test Cases\n",
+ "\n",
+ "* items or total weight is None -> Exception\n",
+ "* items or total weight is 0 -> 0\n",
+ "* General case\n",
+ "\n",
+ "\n",
+ "total_weight = 8\n",
+ "items\n",
+ " v | w\n",
+ " 0 | 0\n",
+ "a 1 | 1\n",
+ "b 3 | 2\n",
+ "c 7 | 4\n",
+ "\n",
+ "max value = 14 \n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Algorithm\n",
+ "\n",
+ "Refer to the [Solution Notebook](). If you are stuck and need a hint, the solution notebook's algorithm discussion might be a good place to start."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Code"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "class Item(object):\n",
+ "\n",
+ " def __init__(self, label, value, weight):\n",
+ " self.label = label\n",
+ " self.value = value\n",
+ " self.weight = weight\n",
+ "\n",
+ " def __repr__(self):\n",
+ " return self.label + ' v:' + str(self.value) + ' w:' + str(self.weight)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "class Knapsack(object):\n",
+ "\n",
+ " def fill_knapsack(self, input_items, total_weight):\n",
+ " # TODO: Implement me\n",
+ " pass"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Unit Test"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "**The following unit test is expected to fail until you solve the challenge.**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# %load test_knapsack_unbounded.py\n",
+ "from nose.tools import assert_equal, assert_raises\n",
+ "\n",
+ "\n",
+ "class TestKnapsack(object):\n",
+ "\n",
+ " def test_knapsack(self):\n",
+ " knapsack = Knapsack()\n",
+ " assert_raises(TypeError, knapsack.fill_knapsack, None, None)\n",
+ " assert_equal(knapsack.fill_knapsack(0, 0), 0)\n",
+ " items = []\n",
+ " items.append(Item(label='a', value=1, weight=1))\n",
+ " items.append(Item(label='b', value=3, weight=2))\n",
+ " items.append(Item(label='c', value=7, weight=4))\n",
+ " total_weight = 8\n",
+ " expected_value = 14\n",
+ " results = knapsack.fill_knapsack(items, total_weight)\n",
+ " total_weight = 7\n",
+ " expected_value = 11\n",
+ " results = knapsack.fill_knapsack(items, total_weight)\n",
+ " assert_equal(results, expected_value)\n",
+ " print('Success: test_knapsack')\n",
+ "\n",
+ "def main():\n",
+ " test = TestKnapsack()\n",
+ " test.test_knapsack()\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " main()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Solution Notebook\n",
+ "\n",
+ "Review the [Solution Notebook]() for a discussion on algorithms and code solutions."
+ ]
+ }
+ ],
+ "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": "3.5.0"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/recursion_dynamic/knapsack_unbounded/knapsack_unbounded_solution.ipynb b/recursion_dynamic/knapsack_unbounded/knapsack_unbounded_solution.ipynb
new file mode 100644
index 0000000..867a00c
--- /dev/null
+++ b/recursion_dynamic/knapsack_unbounded/knapsack_unbounded_solution.ipynb
@@ -0,0 +1,298 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "This notebook was prepared by [Donne Martin](https://github.com/donnemartin). Source and license info is on [GitHub](https://github.com/donnemartin/interactive-coding-challenges)."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Solution Notebook"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Problem: Given a knapsack with a total weight capacity and a list of items with weight w(i) and value v(i), determine the max total value you can carry.\n",
+ "\n",
+ "* [Constraints](#Constraints)\n",
+ "* [Test Cases](#Test-Cases)\n",
+ "* [Algorithm](#Algorithm)\n",
+ "* [Code](#Code)\n",
+ "* [Unit Test](#Unit-Test)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Constraints\n",
+ "\n",
+ "* Can we replace the items once they are placed in the knapsack?\n",
+ " * Yes, this is the unbounded knapsack problem\n",
+ "* Can we split an item?\n",
+ " * No\n",
+ "* Can we get an input item with weight of 0 or value of 0?\n",
+ " * No\n",
+ "* Do we need to return the items that make up the max total value?\n",
+ " * No, just the total value\n",
+ "* Can we assume the inputs are valid?\n",
+ " * No\n",
+ "* Are the inputs in sorted order by val/weight?\n",
+ " * Yes\n",
+ "* Can we assume this fits memory?\n",
+ " * Yes"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Test Cases\n",
+ "\n",
+ "* items or total weight is None -> Exception\n",
+ "* items or total weight is 0 -> 0\n",
+ "* General case\n",
+ "\n",
+ "\n",
+ "total_weight = 8\n",
+ "items\n",
+ " v | w\n",
+ " 0 | 0\n",
+ "a 1 | 1\n",
+ "b 3 | 2\n",
+ "c 7 | 4\n",
+ "\n",
+ "max value = 14 \n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Algorithm\n",
+ "\n",
+ "We'll use bottom up dynamic programming to build a table. \n",
+ "\n",
+ "Taking what we learned with the 0/1 knapsack problem, we could solve the problem like the following:\n",
+ "\n",
+ "\n",
+ "\n",
+ "v = value\n",
+ "w = weight\n",
+ "\n",
+ " j \n",
+ " -------------------------------------------------\n",
+ " | v | w || 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |\n",
+ " -------------------------------------------------\n",
+ " | 0 | 0 || 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
+ " a | 1 | 1 || 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |\n",
+ "i b | 3 | 2 || 0 | 1 | 3 | 4 | 6 | 7 | 9 | 10 | 12 |\n",
+ " c | 7 | 4 || 0 | 1 | 3 | 4 | 7 | 8 | 10 | 11 | 14 |\n",
+ " -------------------------------------------------\n",
+ "\n",
+ "i = row\n",
+ "j = col\n",
+ "\n",
+ "
\n",
+ "\n",
+ "However, unlike the 0/1 knapsack variant, we don't actually need to keep space of O(n * w), where n is the number of items and w is the total weight. We just need a single array that we update after we process each item:\n",
+ "\n",
+ "\n",
+ "\n",
+ " -------------------------------------------------\n",
+ " | v | w || 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |\n",
+ " -------------------------------------------------\n",
+ "\n",
+ " -------------------------------------------------\n",
+ " a | 1 | 1 || 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |\n",
+ " -------------------------------------------------\n",
+ "\n",
+ " -------------------------------------------------\n",
+ " b | 3 | 2 || 0 | 1 | 3 | 4 | 6 | 7 | 9 | 10 | 12 |\n",
+ " -------------------------------------------------\n",
+ "\n",
+ " -------------------------------------------------\n",
+ " c | 7 | 4 || 0 | 1 | 3 | 4 | 7 | 8 | 10 | 11 | 14 |\n",
+ " -------------------------------------------------\n",
+ "\n",
+ "if j >= items[i].weight:\n",
+ " T[j] = max(items[i].value + T[j - items[i].weight],\n",
+ " T[j])\n",
+ "\n",
+ "
\n",
+ "\n",
+ "Complexity:\n",
+ "* Time: O(n * w), where n is the number of items and w is the total weight\n",
+ "* Space: O(w), where w is the total weight"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Code"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Item Class"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "class Item(object):\n",
+ "\n",
+ " def __init__(self, label, value, weight):\n",
+ " self.label = label\n",
+ " self.value = value\n",
+ " self.weight = weight\n",
+ "\n",
+ " def __repr__(self):\n",
+ " return self.label + ' v:' + str(self.value) + ' w:' + str(self.weight)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Knapsack Bottom Up"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "class Knapsack(object):\n",
+ "\n",
+ " def fill_knapsack(self, items, total_weight):\n",
+ " if items is None or total_weight is None:\n",
+ " raise TypeError('items or total_weight cannot be None')\n",
+ " if not items or total_weight == 0:\n",
+ " return 0\n",
+ " num_rows = len(items)\n",
+ " num_cols = total_weight + 1\n",
+ " T = [0] * (num_cols)\n",
+ " for i in range(num_rows):\n",
+ " for j in range(num_cols):\n",
+ " if j >= items[i].weight:\n",
+ " T[j] = max(items[i].value + T[j - items[i].weight],\n",
+ " T[j])\n",
+ " return T[-1]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Unit Test"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Overwriting test_knapsack_unbounded.py\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%writefile test_knapsack_unbounded.py\n",
+ "from nose.tools import assert_equal, assert_raises\n",
+ "\n",
+ "\n",
+ "class TestKnapsack(object):\n",
+ "\n",
+ " def test_knapsack(self):\n",
+ " knapsack = Knapsack()\n",
+ " assert_raises(TypeError, knapsack.fill_knapsack, None, None)\n",
+ " assert_equal(knapsack.fill_knapsack(0, 0), 0)\n",
+ " items = []\n",
+ " items.append(Item(label='a', value=1, weight=1))\n",
+ " items.append(Item(label='b', value=3, weight=2))\n",
+ " items.append(Item(label='c', value=7, weight=4))\n",
+ " total_weight = 8\n",
+ " expected_value = 14\n",
+ " results = knapsack.fill_knapsack(items, total_weight)\n",
+ " total_weight = 7\n",
+ " expected_value = 11\n",
+ " results = knapsack.fill_knapsack(items, total_weight)\n",
+ " assert_equal(results, expected_value)\n",
+ " print('Success: test_knapsack')\n",
+ "\n",
+ "def main():\n",
+ " test = TestKnapsack()\n",
+ " test.test_knapsack()\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " main()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Success: test_knapsack\n"
+ ]
+ }
+ ],
+ "source": [
+ "%run -i test_knapsack_unbounded.py"
+ ]
+ }
+ ],
+ "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": "3.4.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/recursion_dynamic/knapsack_unbounded/test_knapsack_unbounded.py b/recursion_dynamic/knapsack_unbounded/test_knapsack_unbounded.py
new file mode 100644
index 0000000..141c7c8
--- /dev/null
+++ b/recursion_dynamic/knapsack_unbounded/test_knapsack_unbounded.py
@@ -0,0 +1,29 @@
+from nose.tools import assert_equal, assert_raises
+
+
+class TestKnapsack(object):
+
+ def test_knapsack(self):
+ knapsack = Knapsack()
+ assert_raises(TypeError, knapsack.fill_knapsack, None, None)
+ assert_equal(knapsack.fill_knapsack(0, 0), 0)
+ items = []
+ items.append(Item(label='a', value=1, weight=1))
+ items.append(Item(label='b', value=3, weight=2))
+ items.append(Item(label='c', value=7, weight=4))
+ total_weight = 8
+ expected_value = 14
+ results = knapsack.fill_knapsack(items, total_weight)
+ total_weight = 7
+ expected_value = 11
+ results = knapsack.fill_knapsack(items, total_weight)
+ assert_equal(results, expected_value)
+ print('Success: test_knapsack')
+
+def main():
+ test = TestKnapsack()
+ test.test_knapsack()
+
+
+if __name__ == '__main__':
+ main()
\ No newline at end of file