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/TP6_keras_intro.ipynb

@@ -80,7 +80,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "5260add2-2092-4849-b39b-0b4416d60275",
    "metadata": {
     "colab": {
@@ -91,8 +91,8 @@
    },
    "outputs": [],
    "source": [
-    "import tensorflow as tf\n",
     "import numpy as np\n",
+    "import tensorflow as tf\n",
     "\n",
     "tf.keras.utils.set_random_seed(42)\n",
     "fashion_mnist = tf.keras.datasets.fashion_mnist\n",
@@ -2244,7 +2244,7 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "studies",
    "language": "python",
    "name": "python3"
   },
@@ -2258,7 +2258,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.9"
+   "version": "3.13.3"
   }
  },
  "nbformat": 4,