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שנה ב/סמסטר ב/למידת מכונה/תרגולים/תרגול 5/תרגול 5.pdf

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+size 2904472

שנה ב/סמסטר ב/למידת מכונה/תרגולים/תרגול 6/EX06-Linear_Regression.pdf

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+size 4129440

שנה ב/סמסטר ב/למידת מכונה/תרגולים/תרגול 6/iris_train_set.csv

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+sepal length (cm),sepal width (cm),petal length (cm),petal width (cm),iris_type
+6,2.2,5,1.5,2
+6.4,2.8,5.6,2.1,2
+7.7,3,6.1,2.3,2
+6.1,3,4.6,1.4,1
+6.8,3,5.5,2.1,2
+6.1,2.8,4,1.3,1
+6.3,2.7,4.9,1.8,2
+6,3.4,4.5,1.6,1
+6.5,3,5.2,2,2
+6.8,3.2,5.9,2.3,2
+6.1,3,4.9,1.8,2
+5.1,3.4,1.5,0.2,0
+4.4,3,1.3,0.2,0
+5,2.3,3.3,1,1
+5.1,3.3,1.7,0.5,0
+6.3,2.8,5.1,1.5,2
+4.8,3.1,1.6,0.2,0
+6,2.7,5.1,1.6,1
+4.9,3.6,1.4,0.1,0
+4.5,2.3,1.3,0.3,0
+5.5,2.4,3.7,1,1
+6.9,3.2,5.7,2.3,2
+5,3.5,1.6,0.6,0
+4.7,3.2,1.3,0.2,0
+5.6,2.9,3.6,1.3,1
+6,2.2,4,1,1
+6.3,3.3,4.7,1.6,1
+5.8,2.7,4.1,1,1
+5,3.3,1.4,0.2,0
+6.1,2.9,4.7,1.4,1
+5.7,2.6,3.5,1,1
+6.5,2.8,4.6,1.5,1
+4.9,2.5,4.5,1.7,2
+5.5,2.6,4.4,1.2,1
+6.7,3,5.2,2.3,2
+5.8,4,1.2,0.2,0
+6.9,3.1,5.1,2.3,2
+6.4,3.2,4.5,1.5,1
+6.9,3.1,5.4,2.1,2
+5.9,3.2,4.8,1.8,1
+6.2,2.9,4.3,1.3,1
+5.7,2.8,4.5,1.3,1
+5.2,4.1,1.5,0.1,0
+6.5,3,5.8,2.2,2
+6.3,3.4,5.6,2.4,2
+5.7,3.8,1.7,0.3,0
+6.7,2.5,5.8,1.8,2
+5.1,2.5,3,1.1,1
+4.8,3,1.4,0.3,0
+6.2,2.2,4.5,1.5,1
+6.4,2.7,5.3,1.9,2
+5.8,2.7,3.9,1.2,1
+7.4,2.8,6.1,1.9,2
+5.2,3.5,1.5,0.2,0
+5.5,4.2,1.4,0.2,0
+5.9,3,5.1,1.8,2
+6.2,2.8,4.8,1.8,2
+4.6,3.1,1.5,0.2,0
+5.6,3,4.5,1.5,1
+4.6,3.4,1.4,0.3,0
+4.9,3.1,1.5,0.1,0
+6.6,3,4.4,1.4,1
+5.4,3.9,1.3,0.4,0
+4.9,2.4,3.3,1,1
+6.2,3.4,5.4,2.3,2
+5,3,1.6,0.2,0
+6.3,2.3,4.4,1.3,1
+5.7,2.8,4.1,1.3,1
+5.6,2.8,4.9,2,2
+5.1,3.5,1.4,0.2,0
+5.7,2.9,4.2,1.3,1
+5,2,3.5,1,1
+4.8,3.4,1.9,0.2,0
+7.7,2.6,6.9,2.3,2
+6.3,2.5,4.9,1.5,1
+5.1,3.5,1.4,0.3,0
+6.5,3,5.5,1.8,2
+6.3,2.5,5,1.9,2
+4.4,3.2,1.3,0.2,0
+6.7,3,5,1.7,1
+5.4,3.7,1.5,0.2,0
+5,3.5,1.3,0.3,0
+6.7,3.3,5.7,2.1,2
+7.7,3.8,6.7,2.2,2
+5.7,2.5,5,2,2
+4.6,3.2,1.4,0.2,0
+4.7,3.2,1.6,0.2,0
+5,3.4,1.5,0.2,0
+4.8,3.4,1.6,0.2,0
+5.3,3.7,1.5,0.2,0
+6.1,2.6,5.6,1.4,2
+6,3,4.8,1.8,2
+5.5,3.5,1.3,0.2,0
+7.2,3.2,6,1.8,2
+7,3.2,4.7,1.4,1
+5.7,4.4,1.5,0.4,0
+4.3,3,1.1,0.1,0
+6.5,3.2,5.1,2,2
+5.8,2.7,5.1,1.9,2
+6.4,3.2,5.3,2.3,2
+6.1,2.8,4.7,1.2,1
+6,2.9,4.5,1.5,1
+5.8,2.7,5.1,1.9,2
+4.9,3,1.4,0.2,0
+6.6,2.9,4.6,1.3,1
+7.1,3,5.9,2.1,2
+6.4,2.9,4.3,1.3,1
+6.9,3.1,4.9,1.5,1
+4.4,2.9,1.4,0.2,0
+5.7,3,4.2,1.2,1
+5.1,3.7,1.5,0.4,0
+5.9,3,4.2,1.5,1
+5.4,3.4,1.5,0.4,0
+5.6,2.7,4.2,1.3,1
+7.3,2.9,6.3,1.8,2
+6.3,3.3,6,2.5,2
+6.7,3.3,5.7,2.5,2
+5.1,3.8,1.6,0.2,0
+4.9,3.1,1.5,0.2,0
+4.6,3.6,1,0.2,0

שנה ב/סמסטר ב/למידת מכונה/תרגולים/תרגול 6/p2-gradient descent example.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:05:48.346031Z",
+     "start_time": "2023-04-20T17:05:47.733567Z"
+    },
+    "executionInfo": {
+     "elapsed": 6,
+     "status": "ok",
+     "timestamp": 1629221386304,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "LLsxyXlLI2QD"
+   },
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:05:48.362064Z",
+     "start_time": "2023-04-20T17:05:48.348032Z"
+    },
+    "executionInfo": {
+     "elapsed": 285,
+     "status": "ok",
+     "timestamp": 1629221419499,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "pHBkUagMB-lz"
+   },
+   "outputs": [],
+   "source": [
+    "def f(x):\n",
+    "  return x**2 - 10 * x + 5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:05:48.378064Z",
+     "start_time": "2023-04-20T17:05:48.364066Z"
+    },
+    "executionInfo": {
+     "elapsed": 2,
+     "status": "ok",
+     "timestamp": 1629221420535,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "L6NNANM0CDmw"
+   },
+   "outputs": [],
+   "source": [
+    "def dx(x):\n",
+    "  return 2*x - 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:07:27.763925Z",
+     "start_time": "2023-04-20T17:07:27.748921Z"
+    },
+    "executionInfo": {
+     "elapsed": 323,
+     "status": "ok",
+     "timestamp": 1629221422366,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "t5gzE6A27gpc"
+   },
+   "outputs": [],
+   "source": [
+    "alpha = 0.1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:07:28.892134Z",
+     "start_time": "2023-04-20T17:07:28.883140Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 388,
+     "status": "ok",
+     "timestamp": 1629221490432,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "k-4jHRXEtwv-",
+    "outputId": "be44d8c4-61e1-49dd-92d9-65387ad2de52"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch\tx\tdx\tα·dx\n",
+      "0\t0.00\t-10.00\t-1.00\n",
+      "1\t1.00\t-8.00\t-0.80\n",
+      "2\t1.80\t-6.40\t-0.64\n",
+      "3\t2.44\t-5.12\t-0.51\n",
+      "4\t2.95\t-4.10\t-0.41\n"
+     ]
+    }
+   ],
+   "source": [
+    "x=0\n",
+    "\n",
+    "print (\"epoch\\tx\\tdx\\tα·dx\")\n",
+    "for i in range(5):\n",
+    "  print (\"%d\\t%.2f\\t%.2f\\t%.2f\" % (i,x,dx(x),alpha * dx(x)))\n",
+    "  x = x - alpha * dx(x)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:07:32.437947Z",
+     "start_time": "2023-04-20T17:07:32.172466Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 279
+    },
+    "executionInfo": {
+     "elapsed": 520,
+     "status": "ok",
+     "timestamp": 1629221767583,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "VdgZsPbrKppT",
+    "outputId": "f4fc3f38-10a3-48cf-b2a2-ee8296457d5a"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for alpha in [0.01,0.03,0.1,0.3]:\n",
+    "  x=0\n",
+    "  x_history=[x]\n",
+    "\n",
+    "  for i in range(40):\n",
+    "    x = x - alpha * dx(x)\n",
+    "    x_history.append(x)\n",
+    "  \n",
+    "  plt.plot(x_history,label=str(alpha))\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.xlabel('epochs');\n",
+    "plt.ylabel('x');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:08:43.703914Z",
+     "start_time": "2023-04-20T17:08:43.485592Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 279
+    },
+    "executionInfo": {
+     "elapsed": 423,
+     "status": "ok",
+     "timestamp": 1629221789092,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "pYT1jhxQ4xlb",
+    "outputId": "90317d44-7f57-4b54-91f6-4ccef9c1c29e"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for alpha in [1,1.1]:\n",
+    "  x=0\n",
+    "  x_history=[x]\n",
+    "\n",
+    "  for i in range(40):\n",
+    "    x = x - alpha * dx(x)\n",
+    "    x_history.append(x)\n",
+    "  \n",
+    "  plt.plot(x_history,label=str(alpha))\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.xlabel('epochs');\n",
+    "plt.ylabel('x');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "authorship_tag": "ABX9TyM17OYj/yiLkz07ZwoaU0wX",
+   "collapsed_sections": [],
+   "name": "5 gradient descent.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

שנה ב/סמסטר ב/למידת מכונה/תרגולים/תרגול 6/p3-Linear regression with gradient descent.ipynb

@@ -0,0 +1,458 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:25:00.078124Z",
+     "start_time": "2023-04-20T17:24:58.216339Z"
+    },
+    "executionInfo": {
+     "elapsed": 499,
+     "status": "ok",
+     "timestamp": 1629223290319,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "ipR49SaK4oZ8"
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:25:00.882298Z",
+     "start_time": "2023-04-20T17:25:00.842268Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 205
+    },
+    "executionInfo": {
+     "elapsed": 12,
+     "status": "ok",
+     "timestamp": 1629223290320,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "rUuqOpqO4wsS",
+    "outputId": "b25e1201-223c-41f8-ec67-cab69f049e4a"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>sepal length (cm)</th>\n",
+       "      <th>sepal width (cm)</th>\n",
+       "      <th>petal length (cm)</th>\n",
+       "      <th>petal width (cm)</th>\n",
+       "      <th>iris_type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>6.0</td>\n",
+       "      <td>2.2</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6.4</td>\n",
+       "      <td>2.8</td>\n",
+       "      <td>5.6</td>\n",
+       "      <td>2.1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>7.7</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>6.1</td>\n",
+       "      <td>2.3</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>6.1</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>4.6</td>\n",
+       "      <td>1.4</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>6.8</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>2.1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   sepal length (cm)  sepal width (cm)  petal length (cm)  petal width (cm)  \\\n",
+       "0                6.0               2.2                5.0               1.5   \n",
+       "1                6.4               2.8                5.6               2.1   \n",
+       "2                7.7               3.0                6.1               2.3   \n",
+       "3                6.1               3.0                4.6               1.4   \n",
+       "4                6.8               3.0                5.5               2.1   \n",
+       "\n",
+       "   iris_type  \n",
+       "0          2  \n",
+       "1          2  \n",
+       "2          2  \n",
+       "3          1  \n",
+       "4          2  "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv('iris_train_set.csv')\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:25:05.075532Z",
+     "start_time": "2023-04-20T17:25:04.806496Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 279
+    },
+    "executionInfo": {
+     "elapsed": 9,
+     "status": "ok",
+     "timestamp": 1629223290320,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "ZqmORcUP48NH",
+    "outputId": "0373777f-2877-44c0-c983-cf36064d4d98"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='petal length (cm)', ylabel='petal width (cm)'>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "X=df['petal length (cm)']\n",
+    "y=df['petal width (cm)']\n",
+    "sns.scatterplot(data=df,x='petal length (cm)',y='petal width (cm)')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:26:07.462462Z",
+     "start_time": "2023-04-20T17:26:07.445466Z"
+    },
+    "executionInfo": {
+     "elapsed": 8,
+     "status": "ok",
+     "timestamp": 1629223290320,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "6N4RQdmOPP2O"
+   },
+   "outputs": [],
+   "source": [
+    "def plot_reg(w1,w0,X,y):\n",
+    "  sns.scatterplot(x=X.to_numpy().reshape(-1),y=y)\n",
+    "  range_x = np.array([X.min(),X.max()])\n",
+    "  plt.plot(range_x,w1*range_x+w0,color='red');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:25:35.172516Z",
+     "start_time": "2023-04-20T17:25:35.158552Z"
+    },
+    "executionInfo": {
+     "elapsed": 9,
+     "status": "ok",
+     "timestamp": 1629223290321,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "_weh97x1OmEY"
+   },
+   "outputs": [],
+   "source": [
+    "def J(w1,w0,X,y):\n",
+    "  return np.sum((w1*X+w0-y)**2)/len(X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:25:39.238923Z",
+     "start_time": "2023-04-20T17:25:39.225920Z"
+    },
+    "executionInfo": {
+     "elapsed": 8,
+     "status": "ok",
+     "timestamp": 1629223290321,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "gnV88jmnO6hs"
+   },
+   "outputs": [],
+   "source": [
+    "def dw1(w1,w0,X,y):\n",
+    "  return 2 * np.sum((w1*X+w0-y)*X)/len(X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:25:41.981524Z",
+     "start_time": "2023-04-20T17:25:41.962528Z"
+    },
+    "executionInfo": {
+     "elapsed": 8,
+     "status": "ok",
+     "timestamp": 1629223290321,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "dJSqtcD2O6Qk"
+   },
+   "outputs": [],
+   "source": [
+    "def dw0(w1,w0,X,y):\n",
+    "  return 2 * np.sum(w1*X+w0-y)/len(X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:26:13.788441Z",
+     "start_time": "2023-04-20T17:26:13.603442Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 265
+    },
+    "executionInfo": {
+     "elapsed": 1097,
+     "status": "ok",
+     "timestamp": 1629223291410,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "sWyNEkn8PGso",
+    "outputId": "e8e39063-581b-4739-8d96-0b2ccd9366db"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "w1=0\n",
+    "w0=0\n",
+    "alpha=0.01\n",
+    "\n",
+    "plot_reg(w1,w0,X,y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-04-20T17:26:19.415815Z",
+     "start_time": "2023-04-20T17:26:19.232814Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 265
+    },
+    "executionInfo": {
+     "elapsed": 12,
+     "status": "ok",
+     "timestamp": 1629223291411,
+     "user": {
+      "displayName": "koby mike",
+      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiwebWyFla1Q83A7MWAJDkFiPJrOCs6ytetpwh-=s64",
+      "userId": "14272159066583388929"
+     },
+     "user_tz": -180
+    },
+    "id": "T4nBE1C3PGjx",
+    "outputId": "b85b20e8-b5a2-4d7b-d93e-d895f3cdfaa2"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in range(10):\n",
+    "  dw1_ = dw1(w1,w0,X,y)\n",
+    "  dw0_ = dw0(w1,w0,X,y)\n",
+    "\n",
+    "  w1 -= alpha * dw1_\n",
+    "  w0 -= alpha * dw0_\n",
+    "\n",
+    "plot_reg(w1,w0,X,y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "authorship_tag": "ABX9TyOMeBirDhDVft0CxyMur2CK",
+   "collapsed_sections": [],
+   "mount_file_id": "1_xqjT_AmbEbCuYmw5tR5L5t2OansixE7",
+   "name": "6 Linear regression with gradient descent.ipynb",
+   "provenance": [
+    {
+     "file_id": "1iD2zbpgKSdiY3YtSoYU7QXzBNp1G4wAM",
+     "timestamp": 1629222431288
+    }
+   ]
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

שנה ב/סמסטר ב/למידת מכונה/תרגולים/תרגול 7/Ex07-Artificial_Neural_Networks.pdf

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