TensowFLow 1 - Introduction.ipynb

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   "source": [
    "### Anaconda\n",
    "* Package consisting of Python libraries ( internal & external ) & IDEs like Jupyter & Spyder\n",
    "* Jupyter is browser based IDE which connects to python in the backend\n",
    "* Dumps the output from Python backend to browser\n",
    "\n",
    "### Foundations\n",
    "* NumPY\n",
    "* Pandas\n",
    "* matplotlib - graphs & charts\n",
    "\n",
    "### Introduction to TensorFlow\n",
    "* Opensorce software library for numerical computation using data flow graphs\n",
    "* Distributed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ops is like handler to entire tensorflow graphs\n",
    "from tensorflow.python.framework import ops\n",
    "\n",
    "#resets the default graph \n",
    "ops.reset_default_graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "#Get graph handle\n",
    "sess = tf.Session()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_tensor = tf.zeros([1,20])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_var = tf.Variable(tf.zeros([1,20]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "# Different kinds of variables\n",
    "row_dim = 2\n",
    "col_dim = 3 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "# Zero initialized variable\n",
    "zero_var = tf.Variable(tf.zeros([row_dim, col_dim]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "# One initialized variable\n",
    "ones_var = tf.Variable(tf.ones([row_dim, col_dim]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
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   "outputs": [],
   "source": [
    "sess.run(zero_var.initializer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "sess.run(ones_var.initializer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "#init a\n",
    "a = tf.constant(5, name=\"input_a\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "#init b\n",
    "b = tf.constant(3, name=\"input_b\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
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   "outputs": [],
   "source": [
    "#create ops\n",
    "c = tf.multiply(a,b, name=\"mul_c\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "d =tf.add(a,b, name=\"add_d\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "e = tf.add(c,d,name=\"add_e\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
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     "execution_count": 21,
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   ],
   "source": [
    "sess.run(e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
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