Feat: Implement Multi Layer Perceptron from scratch.

 Changes to be committed:
	modified:   LogisticRegressionGluon.ipynb
	new file:   MLPScratch.ipynb

Author: dheeraj-coding

LogisticRegressionGluon.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -33,7 +33,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -45,7 +45,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -62,7 +62,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -73,7 +73,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -84,7 +84,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -94,23 +94,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Epoch 0, acc: 0.805600\n",
-      "Epoch 1, acc: 0.822417\n",
-      "Epoch 2, acc: 0.826817\n",
-      "Epoch 3, acc: 0.831850\n",
-      "Epoch 4, acc: 0.838033\n"
+      "Epoch 0, acc: 0.841133\n",
+      "Epoch 1, acc: 0.844767\n",
+      "Epoch 2, acc: 0.844800\n",
+      "Epoch 3, acc: 0.847500\n",
+      "Epoch 4, acc: 0.849050\n",
+      "Epoch 5, acc: 0.849267\n",
+      "Epoch 6, acc: 0.848650\n",
+      "Epoch 7, acc: 0.849333\n",
+      "Epoch 8, acc: 0.852783\n",
+      "Epoch 9, acc: 0.854133\n"
      ]
     }
    ],
    "source": [
-    "epochs = 5\n",
+    "epochs = 10\n",
     "for epoch in range(epochs):\n",
     "    for X, y in train_iter:\n",
     "        with autograd.record():\n",