Livro NN with Python - Chapter.1 and .2

Chapter01/keras.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using TensorFlow backend.\n"
+     ]
+    }
+   ],
+   "source": [
+    "from keras.models import Sequential \n",
+    "from keras.layers import Dense\n",
+    "from keras import optimizers\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From c:\\Users\\Crrea\\miniconda3\\envs\\neural-network-projects-python\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:74: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = Sequential()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WARNING:tensorflow:From c:\\Users\\Crrea\\miniconda3\\envs\\neural-network-projects-python\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.\n",
+      "\n",
+      "WARNING:tensorflow:From c:\\Users\\Crrea\\miniconda3\\envs\\neural-network-projects-python\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Layer 1\n",
+    "model.add(Dense(units = 4, activation='sigmoid', input_dim = 3))\n",
+    "# Output layer\n",
+    "model.add(Dense(units=1, activation='sigmoid'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "_________________________________________________________________\n",
+      "Layer (type)                 Output Shape              Param #   \n",
+      "=================================================================\n",
+      "dense_1 (Dense)              (None, 4)                 16        \n",
+      "_________________________________________________________________\n",
+      "dense_2 (Dense)              (None, 1)                 5         \n",
+      "=================================================================\n",
+      "Total params: 21\n",
+      "Trainable params: 21\n",
+      "Non-trainable params: 0\n",
+      "_________________________________________________________________\n",
+      "None\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(model.summary())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Loss function keras\n",
+    "sgd = optimizers.SGD(lr=1)\n",
+    "model.compile(loss = 'mean_squared_error', optimizer=sgd)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[0.03039777]\n",
+      " [0.9787922 ]\n",
+      " [0.9621813 ]\n",
+      " [0.03268841]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "X = np.array([[0,0,1],\n",
+    "              [0,1,1],\n",
+    "              [1,0,1],\n",
+    "              [1,1,1]])\n",
+    "y = np.array([[0],[1],[1],[0]])\n",
+    "\n",
+    "# trainer model with fit\n",
+    "model.fit(X, y, epochs=1500, verbose=False)\n",
+    "\n",
+    "print(model.predict(X))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "neural-network-projects-python",
+   "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": "3.6.8"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}