MachineLearning-07.ipynb

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    "#  Coursera: [Machine Learning](https://www.coursera.org/learn/machine-learning) - Week 7\n",
    "\n",
    "Created by Andrew Ng / Stanford University"
   ]
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    "## Table of Content\n",
    "\n",
    "* [Support Vector Machines](#Support-Vector-Machines)\n",
    "   * Large Margin Classification\n",
    "      * Optimization Objective\n",
    "      * Large Margin Intuition\n",
    "      * Mathematics Behind Large Margin Classification\n",
    "   * Kernels\n",
    "      * Kernels I\n",
    "      * Kernels II\n",
    "   * SVMs in Practice\n",
    "      * Using An SVM\n",
    "   * Review"
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   "source": [
    "## Support Vector Machines\n",
    "\n",
    "Welcome to week 7! This week, you will be learning about the support vector machine (SVM) algorithm. SVMs are considered by many to be the most powerful 'black box' learning algorithm, and by posing a cleverly-chosen optimization objective, one of the most widely used learning algorithms today."
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    "### Large Margin Classification\n",
    "\n",
    "#### Optimization Objective\n",
    "\n",
    "-\n",
    "\n",
    "#### Large Margin Intuition\n",
    "\n",
    "-\n",
    "\n",
    "#### Mathematics Behind Large Margin Classification\n",
    "\n",
    "-"
   ]
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   "source": [
    "### Kernels\n",
    "\n",
    "#### Kernels I\n",
    "\n",
    "-\n",
    "\n",
    "#### Kernels II\n",
    "\n",
    "-"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SVMs in Practice\n",
    "\n",
    "#### Using An SVM\n",
    "\n",
    "-"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Review\n",
    "\n",
    "[Lecture12.pdf](lectures/Lecture12.pdf)"
   ]
  }
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