Hello World Files Added

app/hello_world.ipynb

@@ -0,0 +1,67 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "np.random.seed(0)\n",
+    "\n",
+    "values = np.random.randn(100) # array of normally distributed random numbers\n",
+    "s = pd.Series(values) # generate a pandas series\n",
+    "s.plot(kind='hist', title='Normally distributed random values') # hist computes distribution\n",
+    "plt.show()  "
+   ]
+  }
+ ],
+ "metadata": {
+  "interpreter": {
+   "hash": "7b49cb315d7b11d6c04729beccf44e1271f172c154a505ea9702bd82859003b8"
+  },
+  "kernelspec": {
+   "display_name": "Python 3.9.7 ('mlflow')",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.13"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

app/hello_world.py

@@ -0,0 +1 @@
+print("hello world! let's do some ml ops!")