keras approach

Project/simple_approach/simple_twitter_learning.ipynb

@@ -20,6 +20,20 @@
     "from sklearn.preprocessing import MultiLabelBinarizer"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# TODO importing function for sentiment to emoji mapping\n",
+    "def sent2emoji(sentiment_vector: np.array):\n",
+    "    return '🤦'\n",
+    "\n",
+    "def emoji2sent(emoji: str):\n",
+    "    return np.zeros(3)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -1263,7 +1277,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1286,7 +1300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1327,7 +1341,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1336,7 +1350,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1345,7 +1359,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [