Update URL names in ML notebooks to be consistent between tutorials and exercises

Author: dansbecker

learntools/machine_learning/kernels_metadata/ch2/kernel-metadata.json

@@ -1,5 +1,5 @@
 {"title": "Exercise: Explore Your Data",
-  "id": "dansbecker/exercise-exploring-your-data",
+  "id": "dansbecker/exercise-explore-your-data",
   "code_file": "../../nbs/ch2.ipynb",
   "language": "python",
   "kernel_type": "notebook",

learntools/machine_learning/kernels_metadata/ch3/kernel-metadata.json

@@ -1,5 +1,5 @@
 {"title": "Exercise: Your First Machine Learning Model",
-  "id": "dansbecker/exercise-build-your-first-model",
+  "id": "dansbecker/exercise-build-your-first-machine-learning-model",
   "code_file": "../../nbs/ch3.ipynb",
   "language": "python",
   "kernel_type": "notebook",

learntools/machine_learning/kernels_metadata/tut2/kernel-metadata.json

@@ -1,5 +1,5 @@
 {"title": "Explore Your Data",
-  "id": "dansbecker/explore-and-understand-your-data",
+  "id": "dansbecker/explore-your-data",
   "code_file": "../../nbs/tut2.ipynb",
   "language": "python",
   "kernel_type": "notebook",

learntools/machine_learning/kernels_metadata/tut5/kernel-metadata.json

@@ -1,5 +1,5 @@
 {"title": "Underfitting and Overfitting",
-  "id": "dansbecker/underfitting-overfitting-and-model-optimization",
+  "id": "dansbecker/underfitting-and-overfitting",
   "code_file": "../../nbs/tut5.ipynb",
   "language": "python",
   "kernel_type": "notebook",

learntools/machine_learning/nbs/ch2.ipynb

@@ -138,7 +138,7 @@
     "Check out this **[discussion thread](https://www.kaggle.com/learn-forum/60581)** to see what others think or to add your ideas.\n",
     "\n",
     "## Keep Going\n",
-    "Move on to **[Reviewing Your Data](https://www.kaggle.com/dansbecker/your-first-machine-learning-model)** for closer examination and modeling.\n",
+    "Move on to **[Build a Machine Learning Model](https://www.kaggle.com/dansbecker/your-first-machine-learning-model)** with this data.\n",
     "\n",
     "---\n",
     "**[Course Home Page](https://www.kaggle.com/learn/machine-learning)**\n",

learntools/machine_learning/nbs/ch4.ipynb

@@ -277,7 +277,7 @@
    "source": [
     "# Keep Going\n",
     "\n",
-    "Now that you can measure model performance, you are ready to run some experiments comparing different models. The key is to understand **[Underfitting and Overfitting](https://www.kaggle.com/dansbecker/underfitting-overfitting-and-model-optimization)**. It's an especially fun part of machine learning. \n",
+    "Now that you can measure model performance, you are ready to run some experiments comparing different models. The key is to understand **[Underfitting and Overfitting](https://www.kaggle.com/dansbecker/underfitting-and-overfitting)**. It's an especially fun part of machine learning. \n",
     "\n",
     "---\n",
     "**[Course Home Page](https://www.kaggle.com/learn/machine-learning)**\n",

learntools/machine_learning/nbs/tut1.ipynb

@@ -48,7 +48,7 @@
     "The splits and values at the leaves will be determined by the data, so it's time for you to check out the data you will be working with.\n",
     "\n",
     "# Continue\n",
-    "Let's get more specific. It's time to **[Examine Your Data](https://www.kaggle.com/dansbecker/starting-your-ml-project)**.\n",
+    "Let's get more specific. It's time to **[Examine Your Data](https://www.kaggle.com/dansbecker/explore-your-data)**.\n",
     "\n",
     "---\n",
     "**[Course Home Page](https://kaggle.com/learn/machine-learning).**\n"