From 7410454e964326d2fe0fb1809508f6fde49e5dc8 Mon Sep 17 00:00:00 2001
From: glibesyck <gsolodzhuk@gmail.com>
Date: Mon, 1 Jul 2024 12:22:18 +0300
Subject: [PATCH] fresh kernel

---
 .../W1D2_ComparingTasks/W1D2_Tutorial3.ipynb  | 317 ++----------------
 1 file changed, 30 insertions(+), 287 deletions(-)

diff --git a/tutorials/W1D2_ComparingTasks/W1D2_Tutorial3.ipynb b/tutorials/W1D2_ComparingTasks/W1D2_Tutorial3.ipynb
index f34590918..e04f97c9c 100644
--- a/tutorials/W1D2_ComparingTasks/W1D2_Tutorial3.ipynb
+++ b/tutorials/W1D2_ComparingTasks/W1D2_Tutorial3.ipynb
@@ -53,7 +53,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "executionInfo": {
      "elapsed": 156,
      "status": "ok",
@@ -107,31 +106,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {
-     "iopub.execute_input": "2024-07-01T08:21:07.948142Z",
-     "iopub.status.busy": "2024-07-01T08:21:07.910848Z",
-     "iopub.status.idle": "2024-07-01T08:21:16.690736Z",
-     "shell.execute_reply": "2024-07-01T08:21:16.687000Z",
-     "shell.execute_reply.started": "2024-07-01T08:21:07.944091Z"
-    },
     "tags": [
      "hide-input"
     ]
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.0\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.1\u001b[0m\n",
-      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
     "\n",
@@ -155,16 +137,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {
-     "iopub.execute_input": "2024-07-01T08:21:16.702429Z",
-     "iopub.status.busy": "2024-07-01T08:21:16.701930Z",
-     "iopub.status.idle": "2024-07-01T08:21:19.517602Z",
-     "shell.execute_reply": "2024-07-01T08:21:19.516737Z",
-     "shell.execute_reply.started": "2024-07-01T08:21:16.702377Z"
-    },
     "tags": [
      "remove-input"
     ]
@@ -200,16 +175,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2024-07-01T08:21:45.197186Z",
-     "iopub.status.busy": "2024-07-01T08:21:45.196720Z",
-     "iopub.status.idle": "2024-07-01T08:21:47.663917Z",
-     "shell.execute_reply": "2024-07-01T08:21:47.662098Z",
-     "shell.execute_reply.started": "2024-07-01T08:21:45.197151Z"
-    }
-   },
+   "execution_count": null,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# @title Data retrieval\n",
@@ -249,16 +216,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {
-     "iopub.execute_input": "2024-07-01T08:21:52.272861Z",
-     "iopub.status.busy": "2024-07-01T08:21:52.272386Z",
-     "iopub.status.idle": "2024-07-01T08:21:52.689154Z",
-     "shell.execute_reply": "2024-07-01T08:21:52.688246Z",
-     "shell.execute_reply.started": "2024-07-01T08:21:52.272819Z"
-    },
     "tags": [
      "hide-input"
     ]
@@ -276,16 +236,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {
-     "iopub.execute_input": "2024-07-01T08:22:15.407466Z",
-     "iopub.status.busy": "2024-07-01T08:22:15.406846Z",
-     "iopub.status.idle": "2024-07-01T08:22:15.430799Z",
-     "shell.execute_reply": "2024-07-01T08:22:15.429527Z",
-     "shell.execute_reply.started": "2024-07-01T08:22:15.407424Z"
-    }
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -346,16 +299,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {
-     "iopub.execute_input": "2024-07-01T08:23:57.971648Z",
-     "iopub.status.busy": "2024-07-01T08:23:57.968450Z",
-     "iopub.status.idle": "2024-07-01T08:23:58.184596Z",
-     "shell.execute_reply": "2024-07-01T08:23:58.182431Z",
-     "shell.execute_reply.started": "2024-07-01T08:23:57.971507Z"
-    },
     "executionInfo": {
      "elapsed": 628,
      "status": "ok",
@@ -370,22 +316,7 @@
      "remove-input"
     ]
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "736fc14207e84a54a9788fa3b48db3b8",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Tab(children=(Output(), Output()), selected_index=0, titles=('Youtube', 'Bilibili'))"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# @title Video 1: Two-armed bandit\n",
     "\n",
@@ -479,9 +410,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -497,8 +426,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -538,9 +466,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "raise NotImplementedError(\"Student exercise: Calculate regret in worst-case scenario\")\n",
@@ -570,15 +496,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {
-    "execution": {
-     "iopub.execute_input": "2024-07-01T08:28:35.203851Z",
-     "iopub.status.busy": "2024-07-01T08:28:35.176523Z",
-     "iopub.status.idle": "2024-07-01T08:28:36.172942Z",
-     "shell.execute_reply": "2024-07-01T08:28:36.171275Z",
-     "shell.execute_reply.started": "2024-07-01T08:28:35.203670Z"
-    },
     "executionInfo": {
      "elapsed": 559,
      "status": "ok",
@@ -590,23 +509,7 @@
      "user_tz": 240
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 800x600 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "image/png": {
-       "height": 575,
-       "width": 775
-      }
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# to_remove solution\n",
     "t = np.arange(1,101) # Array representing trials from 1 to 100\n",
@@ -636,8 +539,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -671,74 +573,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2024-07-01T08:30:41.780486Z",
-     "iopub.status.busy": "2024-07-01T08:30:41.776499Z",
-     "iopub.status.idle": "2024-07-01T08:30:41.950380Z",
-     "shell.execute_reply": "2024-07-01T08:30:41.948999Z",
-     "shell.execute_reply.started": "2024-07-01T08:30:41.780393Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2fad71dc14a9434387113222c62b727d",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "FloatSlider(value=0.4, description='Left Arm Reward Probability', max=1.0, step=0.01)"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7d4b8e882e9b4881ad6c81d49a1e7361",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "FloatSlider(value=0.6, description='Right Arm Reward Probability', max=1.0, step=0.01)"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "0f2e511b2f1749c9b1410a7efea12279",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Button(description='Simulate!', style=ButtonStyle())"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a174b98c8e8643e99af0e8ad143855d3",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "class BinaryBandit:\n",
     "    \"\"\"\n",
@@ -842,8 +679,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -866,74 +702,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2024-07-01T08:35:00.574756Z",
-     "iopub.status.busy": "2024-07-01T08:35:00.567338Z",
-     "iopub.status.idle": "2024-07-01T08:35:00.694144Z",
-     "shell.execute_reply": "2024-07-01T08:35:00.691447Z",
-     "shell.execute_reply.started": "2024-07-01T08:35:00.574585Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3574e210a12149c49593d9fc2896e428",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "FloatSlider(value=0.2, description='Left Arm Reward Probability', max=1.0, step=0.01)"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ab84e3c530b949ba96882b0d757d0a3a",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "FloatSlider(value=0.8, description='Right Arm Reward Probability', max=1.0, step=0.01)"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "01405dede73547bf8f5b3faab7de726c",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Button(description='Simulate!', style=ButtonStyle())"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "db8f60d93441442ead4aeddaee3d258b",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Output()"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "class SwitchedBinaryBandit:\n",
     "    \"\"\"\n",
@@ -994,9 +765,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -1012,8 +781,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -1033,33 +801,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {
-     "iopub.execute_input": "2024-07-01T08:35:22.422768Z",
-     "iopub.status.busy": "2024-07-01T08:35:22.422258Z",
-     "iopub.status.idle": "2024-07-01T08:35:23.564301Z",
-     "shell.execute_reply": "2024-07-01T08:35:23.562887Z",
-     "shell.execute_reply.started": "2024-07-01T08:35:22.422737Z"
-    }
+    "cellView": "form"
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "45e2ddbb5a4e45c79113b2b548919a76",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Tab(children=(Output(), Output()), selected_index=0, titles=('Youtube', 'Bilibili'))"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# @title Video 2: Meta-RL\n",
     "\n",
@@ -1324,9 +1070,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -1349,8 +1093,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [