Added requirements file and tested the nbs

aws-samples · Nov 3, 2021 · a075206 · a075206
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diff --git a/assignments/DTE-LECTURE-1-ASSIGNMENT-SOLN.ipynb b/assignments/DTE-LECTURE-1-ASSIGNMENT-SOLN.ipynb
diff --git a/assignments/DTE-LECTURE-1-ASSIGNMENT.ipynb b/assignments/DTE-LECTURE-1-ASSIGNMENT.ipynb
diff --git a/assignments/DTE-LECTURE-2-ASSIGNMENT-SOLN.ipynb b/assignments/DTE-LECTURE-2-ASSIGNMENT-SOLN.ipynb
@@ -23,6 +23,15 @@
     "Now that we know how decision trees work, we want to start thinking about ensembling, and how to bring many models together.  In particular, we'll take a look at ExtraTrees, and try to understand explicitly how the bias variance trade-off works."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -q -r ../requirements.txt"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -690,7 +699,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.6.13"
   }
  },
  "nbformat": 4,

diff --git a/assignments/DTE-LECTURE-2-ASSIGNMENT.ipynb b/assignments/DTE-LECTURE-2-ASSIGNMENT.ipynb
@@ -23,6 +23,15 @@
     "Now that we know how decision trees work, we want to start thinking about ensembling, and how to bring many models together.  In particular, we'll take a look at ExtraTrees, and try to understand explicitly how the bias variance trade-off works."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -q -r ../requirements.txt"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -270,7 +279,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.6.13"
   }
  },
  "nbformat": 4,

diff --git a/assignments/DTE-LECTURE-3-ASSIGNMENT-SOLN.ipynb b/assignments/DTE-LECTURE-3-ASSIGNMENT-SOLN.ipynb
@@ -23,6 +23,15 @@
     "We're going to be digging in to random forests, and seeing how they provide extreme improvements in both computational efficiency and generalization errors."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -q -r ../requirements.txt"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -682,7 +691,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.6.13"
   }
  },
  "nbformat": 4,

diff --git a/assignments/DTE-LECTURE-3-ASSIGNMENT.ipynb b/assignments/DTE-LECTURE-3-ASSIGNMENT.ipynb
@@ -23,6 +23,15 @@
     "We're going to be digging in to random forests, and seeing how they provide extreme improvements in both computational efficiency and generalization errors."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -q -r ../requirements.txt"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -269,7 +278,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.6.13"
   }
  },
  "nbformat": 4,

diff --git a/assignments/DTE-LECTURE-4-ASSIGNMENT-SOLN.ipynb b/assignments/DTE-LECTURE-4-ASSIGNMENT-SOLN.ipynb
@@ -23,6 +23,15 @@
     "We'll see how to implement proximities."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -q -r ../requirements.txt"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -432,7 +441,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.6.13"
   }
  },
  "nbformat": 4,

diff --git a/assignments/DTE-LECTURE-4-ASSIGNMENT.ipynb b/assignments/DTE-LECTURE-4-ASSIGNMENT.ipynb
@@ -23,6 +23,15 @@
     "We'll see how to implement proximities."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -q -r ../requirements.txt"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -214,7 +223,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.6.13"
   }
  },
  "nbformat": 4,

diff --git a/assignments/DTE-LECTURE-5-ASSIGNMENT.ipynb b/assignments/DTE-LECTURE-5-ASSIGNMENT.ipynb
@@ -17,12 +17,21 @@
     "Here are the links for the Boosting methods with discussed in the class:\n",
     "* __XGBoost:__ Extreme gradient boosting with [documentation](https://xgboost.readthedocs.io/en/latest/) and [paper](https://arxiv.org/pdf/1603.02754.pdf)\n",
     "* __LightGBM:__ LightGBM with [documentation](https://lightgbm.readthedocs.io/en/latest/) and [paper](https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree.pdf)\n",
-    "* __CatBoost:__ CatBoost with [documentation](https://catboost.ai/docs/concepts/about.html) and [paper](https://arxiv.org/pdf/1706.09516.pdf)\n",
+    "* __CatBoost:__ CatBoost with [documentation](https://catboost.ai/en/docs/) and [paper](https://arxiv.org/pdf/1706.09516.pdf)\n",
     "\n",
     "## This Assignment's Goals\n",
     "This assignment's goal is to use a boosting method on your final project."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -q -r ../requirements.txt"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -509,7 +518,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.6.13"
   }
  },
  "nbformat": 4,

diff --git a/notebooks/final_project/DTE-FINAL-PROJECT.ipynb b/notebooks/final_project/DTE-FINAL-PROJECT.ipynb
@@ -46,6 +46,15 @@
     "- __Time at Center__ - Time at center (0 = less than 30 days; 1 = more than 30 days). This is the value to predict. "
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -q -r ../../requirements.txt"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -58,7 +67,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -104,7 +113,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -258,7 +267,7 @@
        "4                   365               0  "
       ]
      },
-     "execution_count": 2,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -271,7 +280,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -419,7 +428,7 @@
        "4      Blue/White                   210  "
       ]
      },
-     "execution_count": 3,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -440,7 +449,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -461,7 +470,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "scrolled": true
    },
@@ -480,7 +489,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {
     "scrolled": true
    },
@@ -501,7 +510,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -527,7 +536,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.6.13"
   }
  },
  "nbformat": 4,

diff --git a/notebooks/lecture_1/DTE-LECTURE-1-PRUNE.ipynb b/notebooks/lecture_1/DTE-LECTURE-1-PRUNE.ipynb
diff --git a/notebooks/lecture_2/DTE-LECTURE-2-TREE-VARIANCE.ipynb b/notebooks/lecture_2/DTE-LECTURE-2-TREE-VARIANCE.ipynb
diff --git a/notebooks/lecture_3/DTE-LECTURE-3-BAGGING-OVERFIT.ipynb b/notebooks/lecture_3/DTE-LECTURE-3-BAGGING-OVERFIT.ipynb
diff --git a/notebooks/lecture_3/DTE-LECTURE-3-BOOTSTRAP.ipynb b/notebooks/lecture_3/DTE-LECTURE-3-BOOTSTRAP.ipynb
diff --git a/notebooks/lecture_3/DTE-LECTURE-3-RANDOM-FOREST.ipynb b/notebooks/lecture_3/DTE-LECTURE-3-RANDOM-FOREST.ipynb
diff --git a/notebooks/lecture_3/DTE-LECTURE-3-TREE-CORRELATION.ipynb b/notebooks/lecture_3/DTE-LECTURE-3-TREE-CORRELATION.ipynb
diff --git a/notebooks/lecture_4/DTE-LECTURE-4-FEATURE-IMPORTANCE.ipynb b/notebooks/lecture_4/DTE-LECTURE-4-FEATURE-IMPORTANCE.ipynb
diff --git a/notebooks/lecture_4/DTE-LECTURE-4-PERMUTATION-FEATURE-IMP.ipynb b/notebooks/lecture_4/DTE-LECTURE-4-PERMUTATION-FEATURE-IMP.ipynb
@@ -7,6 +7,15 @@
     "![MLU Logo](../../data/MLU_Logo.png)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install -q -r ../../requirements.txt"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -33078,7 +33087,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.6.13"
   }
  },
  "nbformat": 4,

diff --git a/notebooks/lecture_5/DTE-LECTURE-5-BOOSTING.ipynb b/notebooks/lecture_5/DTE-LECTURE-5-BOOSTING.ipynb