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mtpalovic · Apr 1, 2022 · 9437e95 · 9437e95
1 parent 24e96d2
commit 9437e95
Showing 1 changed file with 130 additions and 18 deletions.
diff --git a/nnn.ipynb b/nnn.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "c4b287cf",
    "metadata": {},
    "outputs": [],
@@ -17,7 +17,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "2bdb3b65",
    "metadata": {},
    "outputs": [],
@@ -30,7 +30,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "b54891d4",
    "metadata": {},
    "outputs": [],
@@ -43,39 +43,39 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e9ae3d7e",
+   "id": "86d860b6",
    "metadata": {},
    "source": [
     "$$J = -\\frac{1}{m}\\sum\\limits_{i=1}^{m}y_i \\ln(a_i)+(1-y_i)\\ln(1-a_i)$$"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "cbf5251b",
+   "id": "d088e26a",
    "metadata": {},
    "source": [
     "$$A = \\sigma(w^{T}x + b)$$"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "08c87f20",
+   "id": "b8a4be1b",
    "metadata": {},
    "source": [
     "$$ \\frac{\\partial J}{\\partial w} = \\frac{1}{m}X(A-Y)^T$$"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "8d4fb4ee",
+   "id": "a63eb29c",
    "metadata": {},
    "source": [
     "$$\\frac{\\partial J}{\\partial b} = \\frac{1}{m}\\sum\\limits_{i=1}^{m}(a_i - y_i)$$"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "6ae3724c",
    "metadata": {},
    "outputs": [],
@@ -343,7 +343,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "82a6813c",
    "metadata": {},
    "outputs": [],
@@ -353,43 +353,155 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "87036383",
+   "execution_count": 6,
+   "id": "56824850",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0.7991071 ],\n",
+       "       [0.21605666],\n",
+       "       [0.99981016],\n",
+       "       [0.63657201]])"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "neural_nets.w"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "7a997e9d",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.9364638761160147,\n",
+       " {'d_w': array([[0.13694411],\n",
+       "         [0.03113021],\n",
+       "         [0.22317942],\n",
+       "         [0.10489103]]),\n",
+       "  'd_b': 0.5094444540829945})"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "neural_nets.forward_propagate_vectorised()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "d4af58aa",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.9364638761160151,\n",
+       " {'d_w1': array([[0.13694411],\n",
+       "         [0.03113021],\n",
+       "         [0.22317942],\n",
+       "         [0.10489103]]),\n",
+       "  'd_b1': 0.5094444540829937})"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "neural_nets.forward_propagate_not_vectorised()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "id": "b477ae6f",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Costs after iter 0:0.9364638761160147\n",
+      "Costs after iter 100:0.7803255531585063\n",
+      "Costs after iter 200:0.6509218172574857\n",
+      "Costs after iter 300:0.5456683422196734\n",
+      "Costs after iter 400:0.4612434451386572\n",
+      "Costs after iter 500:0.39406150223948505\n",
+      "Costs after iter 600:0.3406993328908312\n",
+      "Costs after iter 700:0.2981677564601786\n",
+      "Costs after iter 800:0.26401617462743593\n",
+      "Costs after iter 900:0.23631838671023508\n",
+      "Costs after iter 1000:0.2135987513297842\n",
+      "Costs after iter 1100:0.1947417565159418\n",
+      "Costs after iter 1200:0.1789078765441063\n",
+      "Costs after iter 1300:0.1654642564759676\n",
+      "Costs after iter 1400:0.15393114763640522\n",
+      "Costs after iter 1500:0.1439419197826715\n",
+      "Costs after iter 1600:0.13521372798584394\n",
+      "Costs after iter 1700:0.1275261481835068\n",
+      "Costs after iter 1800:0.12070562566821398\n",
+      "Costs after iter 1900:0.1146141145793622\n",
+      "Costs after iter 2000:0.1091407278782687\n",
+      "Costs after iter 2100:0.10419555264293158\n",
+      "Costs after iter 2200:0.0997050297377399\n",
+      "Costs after iter 2300:0.09560847095995492\n",
+      "Costs after iter 2400:0.0918554095589699\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'w': array([[0.27804286],\n",
+       "        [0.02444421],\n",
+       "        [0.06776185],\n",
+       "        [0.1587318 ]]),\n",
+       " 'b': -2.468142975034734}"
+      ]
+     },
+     "execution_count": 9,
+     "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"
+    }
+   ],
    "source": [
     "neural_nets.gradient_descent()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9281c6e1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {