chore: clean up code structure and remove unused code blocks

M2/Reinforcement Learning/project/Project.ipynb

@@ -0,0 +1,80 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "7e37429a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ale_py\n",
+    "import gymnasium as gym\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "85ff0eb4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "A.L.E: Arcade Learning Environment (version 0.11.2+ecc1138)\n",
+      "[Powered by Stella]\n"
+     ]
+    },
+    {
+     "ename": "",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31mLe noyau s’est bloqué lors de l’exécution du code dans une cellule active ou une cellule précédente. \n",
+      "\u001b[1;31mVeuillez vérifier le code dans la ou les cellules pour identifier une cause possible de l’échec. \n",
+      "\u001b[1;31mCliquez <a href='https://aka.ms/vscodeJupyterKernelCrash'>ici</a> pour plus d’informations. \n",
+      "\u001b[1;31mPour plus d’informations, consultez Jupyter <a href='command:jupyter.viewOutput'>log</a>."
+     ]
+    }
+   ],
+   "source": [
+    "gym.register_envs(ale_py)\n",
+    "\n",
+    "env = gym.make(\"ALE/Tennis-v5\", render_mode=\"human\")\n",
+    "obs, info = env.reset()\n",
+    "obs, reward, terminated, truncated, info = env.step(env.action_space.sample())\n",
+    "env.close()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "89633751",
+   "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": "3.13.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

M2/Reinforcement Learning/project/pyproject.toml

@@ -0,0 +1,11 @@
+[project]
+name = "project"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+dependencies = [
+    "ale-py>=0.11.2",
+    "numpy>=2.2.5",
+    "pyclustertend>=1.4.9",
+]