Refactor code in numerical methods notebooks

- Updated import order in Point_Fixe.ipynb for consistency.
- Changed lambda functions to regular function definitions for clarity in Point_Fixe.ipynb.
- Added numpy import in TP1_EDO_EulerExp.ipynb, TP2_Lokta_Volterra.ipynb, and TP3_Convergence.ipynb for better readability.
- Modified for loops in TP1_EDO_EulerExp.ipynb and TP2_Lokta_Volterra.ipynb to include strict=False for compatibility with future Python versions.

M1/Statistical Learning/TP4_Ridge_Lasso_and_CV.ipynb

@@ -48,7 +48,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2025-03-26T10:34:01.222808Z",
@@ -433,9 +433,9 @@
     }
    ],
    "source": [
+    "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "import pandas as pd  # dataframes are in pandas\n",
-    "import matplotlib.pyplot as plt\n",
     "\n",
     "hitters = pd.read_csv(\"data/Hitters.csv\", index_col=\"Name\")\n",
     "\n",
@@ -896,11 +896,11 @@
    "source": [
     "# Hint for Question (4) :\n",
     "ex = pd.DataFrame(\n",
-    "    dict(\n",
-    "        nom=[\"Alice\", \"Nicolas\", \"Jean\"],\n",
-    "        age=[19, np.NaN, np.NaN],\n",
-    "        exam=[15, 14, np.NaN],\n",
-    "    )\n",
+    "    {\n",
+    "        \"nom\": [\"Alice\", \"Nicolas\", \"Jean\"],\n",
+    "        \"age\": [19, np.NaN, np.NaN],\n",
+    "        \"exam\": [15, 14, np.NaN],\n",
+    "    }\n",
     ")\n",
     "\n",
     "print(\"data : \\n\", ex)\n",
@@ -2545,7 +2545,7 @@
     "\n",
     "MSEs = []\n",
     "for name, estimator in zip(\n",
-    "    [\"LassoCV\", \"LassoBIC\", \"RidgeCV\", \"OLS\"], [lassoCV, lassoBIC, ridgeCV, linReg]\n",
+    "    [\"LassoCV\", \"LassoBIC\", \"RidgeCV\", \"OLS\"], [lassoCV, lassoBIC, ridgeCV, linReg], strict=False\n",
     "):\n",
     "    y_pred = estimator.predict(Xtest)\n",
     "    MSE = mean_squared_error(Ytest, y_pred)\n",