Merge pull request VedangW#2 from maigar/master

Changed a bit in assn2 and added Iris.csv

python-assn/assn-02/numpy.ipynb → python-assn/assn-02/Assignment2.ipynb

@@ -155,7 +155,30 @@
     "# If y contains 0, y1 should have (1,0,0)\n",
     "# If y contains 1, y1 should have (0,1,0)\n",
     "# If y contains 2, y1 should have (0,0,1)\n",
-    "# This type of encoding is known as one-hot encoding"
+    "# This type of encoding is known as one-hot encoding\n",
+    "#################################\n",
+    "\n",
+    "#################################"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "A=np.random.randint(100,size=(32,64,3))\n",
+    "# Convert A into shape (1,32,64,3) without using np.reshape()\n",
+    "#################################\n",
+    "\n",
+    "#################################"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Expected Output:<br>(1,32,64,3)"
    ]
   }
  ],

python-assn/assn-02/Iris.csv

@@ -0,0 +1,150 @@
+5.1,3.5,1.4,0.2,0
+4.9,3,1.4,0.2,0
+4.7,3.2,1.3,0.2,0
+4.6,3.1,1.5,0.2,0
+5,3.6,1.4,0.2,0
+5.4,3.9,1.7,0.4,0
+4.6,3.4,1.4,0.3,0
+5,3.4,1.5,0.2,0
+4.4,2.9,1.4,0.2,0
+4.9,3.1,1.5,0.1,0
+5.4,3.7,1.5,0.2,0
+4.8,3.4,1.6,0.2,0
+4.8,3,1.4,0.1,0
+4.3,3,1.1,0.1,0
+5.8,4,1.2,0.2,0
+5.7,4.4,1.5,0.4,0
+5.4,3.9,1.3,0.4,0
+5.1,3.5,1.4,0.3,0
+5.7,3.8,1.7,0.3,0
+5.1,3.8,1.5,0.3,0
+5.4,3.4,1.7,0.2,0
+5.1,3.7,1.5,0.4,0
+4.6,3.6,1,0.2,0
+5.1,3.3,1.7,0.5,0
+4.8,3.4,1.9,0.2,0
+5,3,1.6,0.2,0
+5,3.4,1.6,0.4,0
+5.2,3.5,1.5,0.2,0
+5.2,3.4,1.4,0.2,0
+4.7,3.2,1.6,0.2,0
+4.8,3.1,1.6,0.2,0
+5.4,3.4,1.5,0.4,0
+5.2,4.1,1.5,0.1,0
+5.5,4.2,1.4,0.2,0
+4.9,3.1,1.5,0.1,0
+5,3.2,1.2,0.2,0
+5.5,3.5,1.3,0.2,0
+4.9,3.1,1.5,0.1,0
+4.4,3,1.3,0.2,0
+5.1,3.4,1.5,0.2,0
+5,3.5,1.3,0.3,0
+4.5,2.3,1.3,0.3,0
+4.4,3.2,1.3,0.2,0
+5,3.5,1.6,0.6,0
+5.1,3.8,1.9,0.4,0
+4.8,3,1.4,0.3,0
+5.1,3.8,1.6,0.2,0
+4.6,3.2,1.4,0.2,0
+5.3,3.7,1.5,0.2,0
+5,3.3,1.4,0.2,0
+7,3.2,4.7,1.4,1
+6.4,3.2,4.5,1.5,1
+6.9,3.1,4.9,1.5,1
+5.5,2.3,4,1.3,1
+6.5,2.8,4.6,1.5,1
+5.7,2.8,4.5,1.3,1
+6.3,3.3,4.7,1.6,1
+4.9,2.4,3.3,1,1
+6.6,2.9,4.6,1.3,1
+5.2,2.7,3.9,1.4,1
+5,2,3.5,1,1
+5.9,3,4.2,1.5,1
+6,2.2,4,1,1
+6.1,2.9,4.7,1.4,1
+5.6,2.9,3.6,1.3,1
+6.7,3.1,4.4,1.4,1
+5.6,3,4.5,1.5,1
+5.8,2.7,4.1,1,1
+6.2,2.2,4.5,1.5,1
+5.6,2.5,3.9,1.1,1
+5.9,3.2,4.8,1.8,1
+6.1,2.8,4,1.3,1
+6.3,2.5,4.9,1.5,1
+6.1,2.8,4.7,1.2,1
+6.4,2.9,4.3,1.3,1
+6.6,3,4.4,1.4,1
+6.8,2.8,4.8,1.4,1
+6.7,3,5,1.7,1
+6,2.9,4.5,1.5,1
+5.7,2.6,3.5,1,1
+5.5,2.4,3.8,1.1,1
+5.5,2.4,3.7,1,1
+5.8,2.7,3.9,1.2,1
+6,2.7,5.1,1.6,1
+5.4,3,4.5,1.5,1
+6,3.4,4.5,1.6,1
+6.7,3.1,4.7,1.5,1
+6.3,2.3,4.4,1.3,1
+5.6,3,4.1,1.3,1
+5.5,2.5,4,1.3,1
+5.5,2.6,4.4,1.2,1
+6.1,3,4.6,1.4,1
+5.8,2.6,4,1.2,1
+5,2.3,3.3,1,1
+5.6,2.7,4.2,1.3,1
+5.7,3,4.2,1.2,1
+5.7,2.9,4.2,1.3,1
+6.2,2.9,4.3,1.3,1
+5.1,2.5,3,1.1,1
+5.7,2.8,4.1,1.3,1
+6.3,3.3,6,2.5,2
+5.8,2.7,5.1,1.9,2
+7.1,3,5.9,2.1,2
+6.3,2.9,5.6,1.8,2
+6.5,3,5.8,2.2,2
+7.6,3,6.6,2.1,2
+4.9,2.5,4.5,1.7,2
+7.3,2.9,6.3,1.8,2
+6.7,2.5,5.8,1.8,2
+7.2,3.6,6.1,2.5,2
+6.5,3.2,5.1,2,2
+6.4,2.7,5.3,1.9,2
+6.8,3,5.5,2.1,2
+5.7,2.5,5,2,2
+5.8,2.8,5.1,2.4,2
+6.4,3.2,5.3,2.3,2
+6.5,3,5.5,1.8,2
+7.7,3.8,6.7,2.2,2
+7.7,2.6,6.9,2.3,2
+6,2.2,5,1.5,2
+6.9,3.2,5.7,2.3,2
+5.6,2.8,4.9,2,2
+7.7,2.8,6.7,2,2
+6.3,2.7,4.9,1.8,2
+6.7,3.3,5.7,2.1,2
+7.2,3.2,6,1.8,2
+6.2,2.8,4.8,1.8,2
+6.1,3,4.9,1.8,2
+6.4,2.8,5.6,2.1,2
+7.2,3,5.8,1.6,2
+7.4,2.8,6.1,1.9,2
+7.9,3.8,6.4,2,2
+6.4,2.8,5.6,2.2,2
+6.3,2.8,5.1,1.5,2
+6.1,2.6,5.6,1.4,2
+7.7,3,6.1,2.3,2
+6.3,3.4,5.6,2.4,2
+6.4,3.1,5.5,1.8,2
+6,3,4.8,1.8,2
+6.9,3.1,5.4,2.1,2
+6.7,3.1,5.6,2.4,2
+6.9,3.1,5.1,2.3,2
+5.8,2.7,5.1,1.9,2
+6.8,3.2,5.9,2.3,2
+6.7,3.3,5.7,2.5,2
+6.7,3,5.2,2.3,2
+6.3,2.5,5,1.9,2
+6.5,3,5.2,2,2
+6.2,3.4,5.4,2.3,2
+5.9,3,5.1,1.8,2