update parameter deep learning.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# GRADED FUNCTION: update_parameters\n",
    "\n",
    "def update_parameters(parameters, grads, learning_rate):\n",
    "    \"\"\"\n",
    "    Update parameters using gradient descent\n",
    "    \n",
    "    Arguments:\n",
    "    parameters -- python dictionary containing your parameters \n",
    "    grads -- python dictionary containing your gradients, output of L_model_backward\n",
    "    \n",
    "    Returns:\n",
    "    parameters -- python dictionary containing your updated parameters \n",
    "                  parameters[\"W\" + str(l)] = ... \n",
    "                  parameters[\"b\" + str(l)] = ...\n",
    "    \"\"\"\n",
    "    \n",
    "    L = len(parameters) // 2 # number of layers in the neural network\n",
    "\n",
    "    # Update rule for each parameter. Use a for loop.\n",
    "    ### START CODE HERE ### (≈ 3 lines of code)\n",
    "    for l in range(L):\n",
    "        parameters[\"W\" + str(l + 1)] = parameters[\"W\" + str(l + 1)] - learning_rate * grads[\"dW\" + str(l + 1)]\n",
    "        parameters[\"b\" + str(l + 1)] = parameters[\"b\" + str(l + 1)] - learning_rate * grads[\"db\" + str(l + 1)]\n",
    "    ### END CODE HERE ###\n",
    "        \n",
    "    return parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "parameters, grads = update_parameters_test_case()\n",
    "parameters = update_parameters(parameters, grads, 0.1)\n",
    "\n",
    "print (\"W1 = \" + str(parameters[\"W1\"]))\n",
    "print (\"b1 = \" + str(parameters[\"b1\"]))\n",
    "print (\"W2 = \" + str(parameters[\"W2\"]))\n",
    "print (\"b2 = \" + str(parameters[\"b2\"]))\n",
    "print (\"W3 = \" + str(parameters[\"W3\"]))\n",
    "print (\"b3 = \" + str(parameters[\"b3\"]))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}