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h9h · Jun 7, 2020 · 15f61b8 · 15f61b8
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diff --git a/Activation-functions.ipynb b/Activation-functions.ipynb
diff --git a/logistic-regression-titanic.ipynb b/logistic-regression-titanic.ipynb
@@ -539,6 +539,13 @@
    "source": [
     "print(set([t.split(',')[1].split('.')[0] for t in train.Name]))"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {

diff --git a/magic.ipynb b/magic.ipynb
@@ -2,56 +2,25 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Populating the interactive namespace from numpy and matplotlib\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%pylab inline"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x7f10a8257790>"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plt.scatter([0,1],[1,1])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -60,45 +29,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "CPU times: user 205 ms, sys: 28.4 ms, total: 233 ms\n",
-      "Wall time: 232 ms\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "-2677412158475480443"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "%time np.sum([x**x for x in np.arange(0,1000000)])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "232 ms ± 1.67 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%timeit np.sum([x**x for x in np.arange(0,1000000)])"
    ]

diff --git a/pca-vs-tsne.ipynb b/pca-vs-tsne.ipynb