Perform Softmax Transformation.ipynb

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   "source": [
    "**Softmax regression** is a method in machine learning which allows for the classification of an input into discrete classes. Unlike the commonly used logistic regression, which can only perform binary classifications, softmax allows for classification into any number of possible classes."
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "<img src=\"data/Softmax.png\">"
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   "source": [
    "import numpy as np"
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   "source": [
    "arrayx = np.array([2,1,0.1])"
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      "[7.3890560989306504, 2.7182818284590451, 1.1051709180756477]\n",
      "11.2125088455\n"
     ]
    }
   ],
   "source": [
    "# Compute Exponential of Each Element\n",
    "exps = [np.exp(i) for i in arrayx]\n",
    "print(exps)\n",
    "# Take sum of the Exponentials \n",
    "sum_of_exps = sum(exps)\n",
    "# Divide Each element by the sum of Exponentials\n",
    "print(sum_of_exps)\n",
    "softmax = [j/sum_of_exps for j in exps]"
   ]
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   "cell_type": "code",
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   "metadata": {},
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     "text": [
      "[0.6590011388859679, 0.2424329707047139, 0.09856589040931818]\n"
     ]
    }
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   "source": [
    "print(softmax)"
   ]
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    "sum(softmax)"
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://medium.com/@awjuliani/simple-softmax-in-python-tutorial-d6b4c4ed5c16"
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  }
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