tweak code

Author: gitName

learn-pr/azure/test-machine-learning-models/notebooks/5-3-exercise-feature-normalization.ipynb

@@ -57,9 +57,6 @@
     "import numpy as np\n",
     "\n",
     "# Train model using Gradient Descent\n",
-    "# This method uses custom code that will print out progress as training advances.\n",
-    "# You don't need to inspect how this works for these exercises, but if you are\n",
-    "# curious, you can find it in out GitHub repository\n",
     "model = gradient_descent(data.month_old_when_trained, data.mean_rescues_per_year, learning_rate=5E-4, number_of_iterations=8000)\n"
    ]
   },

learn-pr/azure/test-machine-learning-models/notebooks/5-5-exercise-test-training-datasets.ipynb

@@ -50,29 +50,31 @@
    "outputs": [],
    "source": [
     "import statsmodels.formula.api as smf\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
     "\n",
     "# First, we define our formula using a special syntax\n",
     "# This says that rescues_last_year is explained by weight_last_year\n",
     "formula = \"rescues_last_year ~ weight_last_year\"\n",
     "\n",
     "model = smf.ols(formula = formula, data = data).fit()\n",
     "\n",
+    "# Extract x and y values\n",
     "x = data[\"weight_last_year\"]\n",
     "y = data[\"rescues_last_year\"]\n",
     "\n",
-    "# Create scatter plot and trendline\n",
+    "# Scatter plot of the data and trendline\n",
     "plt.figure(figsize=(8, 6))\n",
-    "plt.scatter(x, y, label=\"Data\", alpha=0.7)\n",
+    "plt.scatter(x, y, alpha=0.7, label=\"Data\")\n",
     "\n",
     "x_vals = np.linspace(x.min(), x.max(), 100)\n",
-    "x_vals_df = pandas.DataFrame({\"month_old_when_trained\": x_vals})\n",
-    "y_preds = model_norm.predict(x_vals_df)\n",
+    "y_vals = model.params[1] * x_vals + model.params[0]  # Slope * x + Intercept\n",
     "\n",
-    "plt.plot(x_vals, y_preds, color=\"red\", label=\"Trendline\")\n",
+    "plt.plot(x_vals, y_vals, color=\"red\", label=\"Trendline (Linear Regression)\")\n",
     "\n",
-    "plt.xlabel(\"Weight last year\")\n",
-    "plt.ylabel(\"Mean Rescues Per Year\")\n",
-    "plt.title(\"Rescues last eyar\")\n",
+    "plt.xlabel(\"Weight Last Year\")\n",
+    "plt.ylabel(\"Rescues Last Year\")\n",
+    "plt.title(\"Rescues vs Weight with Linear Trendline\")\n",
     "plt.legend()\n",
     "plt.grid(True)\n",
     "plt.tight_layout()\n",