add deep lgbm params to tutorial notebook comments

Author: ndharasz

example_model.ipynb

@@ -126,12 +126,21 @@
         "# Train model\n",
         "import lightgbm as lgb\n",
         "model = lgb.LGBMRegressor(\n",
-        "    n_estimators=2000,  # If you want to use a larger model we've found 20_000 trees to be better\n",
-        "    learning_rate=0.01, # and a learning rate of 0.001\n",
-        "    max_depth=5, # and max_depth=6\n",
-        "    num_leaves=2**5-1, # and num_leaves of 2**6-1\n",
+        "    n_estimators=2000,\n",
+        "    learning_rate=0.01,\n",
+        "    max_depth=5,\n",
+        "    num_leaves=2**5-1,\n",
         "    colsample_bytree=0.1\n",
         ")\n",
+        "# We've found the following \"deep\" parameters perform much better, but they require much more CPU and RAM\n",
+        "# model = lgb.LGBMRegressor(\n",
+        "#     n_estimators=2 30_000,\n",
+        "#     learning_rate=0.001,\n",
+        "#     max_depth=10,\n",
+        "#     num_leaves=2**10,\n",
+        "#     colsample_bytree=0.1\n",
+        "#     min_data_in_leaf=10000,\n",
+        "# )\n",
         "model.fit(\n",
         "    train[features],\n",
         "    train[\"target\"]\n",