diff --git a/Lösung_N/AB1.ipynb b/Lösung_N/AB1.ipynb
new file mode 100644
index 0000000..f1b3c81
--- /dev/null
+++ b/Lösung_N/AB1.ipynb
@@ -0,0 +1,1034 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "abb2a68a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "581c7c84",
+   "metadata": {},
+   "source": [
+    "a)\n",
+    "Vier Datenpunkte pro Iris-Art\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "7978a573",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#b) \n",
+    "iris_data= np.loadtxt(\"../supplement_files/iris.csv\", delimiter=\",\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "a1122915",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#c)\n",
+    "iris_data\n",
+    "X = iris_data[:,:4]\n",
+    "T = iris_data[:,4]\n",
+    "# Zeilenvektoren in Spaltenvektoren konvertieren\n",
+    "X = X.T"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f5d22693",
+   "metadata": {},
+   "source": [
+    "d)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "5f5b8df7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#e)\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "plt.scatter(X[0], X[1],)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "a21fe3c8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#f)\n",
+    "plt.scatter(X[0], X[1],c=T, cmap=plt.cm.prism)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "c4882c4f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "data": [
+        {
+         "hovertemplate": "x=%{x}<br>y=%{y}<br>z=%{z}<br>color=%{marker.color}<extra></extra>",
+         "legendgroup": "",
+         "marker": {
+          "color": {
+           "bdata": "AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABA",
+           "dtype": "f8"
+          },
+          "coloraxis": "coloraxis",
+          "symbol": "circle"
+         },
+         "mode": "markers",
+         "name": "",
+         "scene": "scene",
+         "showlegend": false,
+         "type": "scatter3d",
+         "x": {
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+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
+          },
+          "autotypenumbers": "strict",
+          "coloraxis": {
+           "colorbar": {
+            "outlinewidth": 0,
+            "ticks": ""
+           }
+          },
+          "colorscale": {
+           "diverging": [
+            [
+             0,
+             "#8e0152"
+            ],
+            [
+             0.1,
+             "#c51b7d"
+            ],
+            [
+             0.2,
+             "#de77ae"
+            ],
+            [
+             0.3,
+             "#f1b6da"
+            ],
+            [
+             0.4,
+             "#fde0ef"
+            ],
+            [
+             0.5,
+             "#f7f7f7"
+            ],
+            [
+             0.6,
+             "#e6f5d0"
+            ],
+            [
+             0.7,
+             "#b8e186"
+            ],
+            [
+             0.8,
+             "#7fbc41"
+            ],
+            [
+             0.9,
+             "#4d9221"
+            ],
+            [
+             1,
+             "#276419"
+            ]
+           ],
+           "sequential": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        }
+       }
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#3b)\n",
+    "import plotly.express as px\n",
+    "fig = px.scatter_3d(X, X[0], X[1], X[2], color=T, color_discrete_map=plt.cm.prism)\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7c79c288",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "nnw (3.14.x)",
+   "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": "3.14.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}