Merge pull request #5 from LDSSA/batch2

Batch2
LDSSA · Aug 11, 2018 · 5923e12 · 5923e12
2 parents 794e773 + ad34b66
commit 5923e12
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Showing 6 changed files with 315 additions and 201 deletions.
diff --git a/Deserialize and use.ipynb b/Deserialize and use.ipynb
@@ -8,7 +8,8 @@
    "source": [
     "import pickle\n",
     "import json\n",
-    "import pandas as pd"
+    "import pandas as pd\n",
+    "from sklearn.externals import joblib"
    ]
   },
   {
@@ -34,7 +35,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,34 +47,33 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now let's get that pipeline un-pickled:"
+    "And now let's un-pickle the dtypes as well:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
-    "with open('pipeline.pickle', 'rb') as fh:\n",
-    "    pipeline = pickle.load(fh)"
+    "with open('dtypes.pickle', 'rb') as fh:\n",
+    "    dtypes = pickle.load(fh)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "And now let's un-pickle the dtypes as well:"
+    "Finally let's get reload the pipeline"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
-    "with open('dtypes.pickle', 'rb') as fh:\n",
-    "    dtypes = pickle.load(fh)"
+    "pipeline = joblib.load('pipeline.pickle')"
    ]
   },
   {
@@ -96,7 +96,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -115,7 +115,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -170,7 +170,7 @@
        "0       3  male  22.0      1      0  7.25  None        S"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -188,16 +188,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array([[ 0.90735821,  0.09264179]])"
+       "array([[0.90499548, 0.09500452]])"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -223,14 +223,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "the observation has 0.09264179297127445 probability of survival\n"
+      "the observation has 0.09500452074453275 probability of survival\n"
      ]
     }
    ],
@@ -262,7 +262,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,