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falcalde21 · Nov 3, 2019 · c300b03 · c300b03
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diff --git a/Hw3/1.png b/Hw3/1.png
diff --git a/Hw3/2.png b/Hw3/2.png
diff --git a/Hw3/HW3 Solution.ipynb b/Hw3/HW3 Solution.ipynb
diff --git a/Hw3/HW3 Solution_bkp.ipynb b/Hw3/HW3 Solution_bkp.ipynb
diff --git a/Hw3/Q1.ipynb b/Hw3/Q1.ipynb
diff --git a/Hw3/Q2.ipynb b/Hw3/Q2.ipynb
diff --git a/Hw3/Untitled.ipynb b/Hw3/Untitled.ipynb
@@ -0,0 +1,125 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn import datasets\n",
+    "sklearn.datasets.load_iris()\n",
+    "iris = sklearn.datasets.load_iris()\n",
+    "X = iris.data[:, :2]\n",
+    "y = (iris.target != 0) * 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(150,)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(150, 2)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "numpy.ndarray"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "numpy.ndarray"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(y)"
+   ]
+  },
+  {
+   "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Hw3/test.ipynb b/Hw3/test.ipynb
diff --git a/Hw3/tmp.ipynb b/Hw3/tmp.ipynb
@@ -0,0 +1,62 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scipy import linalg\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "from matplotlib import colors\n",
+    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# #############################################################################\n",
+    "# Colormap\n",
+    "cmap = colors.LinearSegmentedColormap(\n",
+    "    'red_blue_classes',\n",
+    "    {'red': [(0, 1, 1), (1, 0.7, 0.7)],\n",
+    "     'green': [(0, 0.7, 0.7), (1, 0.7, 0.7)],\n",
+    "     'blue': [(0, 0.7, 0.7), (1, 1, 1)]})\n",
+    "plt.cm.register_cmap(cmap=cmap)"
+   ]
+  },
+  {
+   "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/L10/cs229-notes7b_GMM_EM.pdf b/L10/cs229-notes7b_GMM_EM.pdf
diff --git a/L2/todo.md b/L2/todo.md
@@ -0,0 +1,7 @@
+https://peterroelants.github.io/posts/multivariate-normal-primer/
+https://www.youtube.com/watch?v=eho8xH3E6mE
+https://www.youtube.com/watch?v=ppd4c96hHH8
+https://www.youtube.com/watch?v=TC0ZAX3DA88
+https://www.youtube.com/watch?v=a2t2EQd5SC4
+http://aishack.in/tutorials/generating-multivariate-gaussian-random/
+http://fourier.eng.hmc.edu/e161/lectures/gaussianprocess/node7.html
diff --git a/Oct_30_SVM2/SmoSch04_tutorial2.pdf b/Oct_30_SVM2/SmoSch04_tutorial2.pdf
diff --git a/ToDo/cs229-notes3.pdf → Oct_30_SVM2/cs229-notes3.pdf b/ToDo/cs229-notes3.pdf → Oct_30_SVM2/cs229-notes3.pdf
diff --git a/Oct_30_SVM2/notes.md b/Oct_30_SVM2/notes.md
@@ -0,0 +1,4 @@
+1. Ng video+notes
+2. Deniz video
+3. tutorial2. related to cs231n SVM
+4. cs231n SVM
diff --git a/Oct_30_SVM2/svmtutorial.pdf b/Oct_30_SVM2/svmtutorial.pdf
diff --git a/Tips/notes.md b/Tips/notes.md
@@ -0,0 +1 @@
+* Always shuffle dataset for kfold (HW3 Q1)
diff --git a/ToDo/error-analysis.pdf b/ToDo/error-analysis.pdf