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Commit da2b27a9 by Paktalin
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class 30 is done

parent b0bf61dc
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Showing with 215 additions and 25 deletions
5_polynomial_regression.ipynb
...@@ -178,7 +178,7 @@ ...@@ -178,7 +178,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.5.5" "version": "3.6.5"
} }
}, },
"nbformat": 4, "nbformat": 4,
......
6_systolic_blood_pressure.ipynb
...@@ -259,7 +259,7 @@ ...@@ -259,7 +259,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.5.5" "version": "3.6.5"
} }
}, },
"nbformat": 4, "nbformat": 4,
......
7_overfitting.ipynb
This source diff could not be displayed because it is too large. You can view the blob instead.
8_l2_regularization.ipynb
...@@ -2,17 +2,19 @@ ...@@ -2,17 +2,19 @@
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 103,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"import numpy as np\n", "import numpy as np\n",
"import matplotlib.pyplot as plt" "import matplotlib.pyplot as plt\n",
"from jupyterthemes import jtplot\n",
"jtplot.style(theme='gruvboxd')"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 104,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -24,7 +26,7 @@ ...@@ -24,7 +26,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 105,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -35,14 +37,14 @@ ...@@ -35,14 +37,14 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 106,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
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\n", 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\n",
"text/plain": [ "text/plain": [
"<Figure size 432x288 with 1 Axes>" "<Figure size 460.8x403.2 with 1 Axes>"
] ]
}, },
"metadata": {}, "metadata": {},
...@@ -56,7 +58,7 @@ ...@@ -56,7 +58,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 107,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -66,7 +68,7 @@ ...@@ -66,7 +68,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 108,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -77,14 +79,14 @@ ...@@ -77,14 +79,14 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": 109,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"image/png": 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\n", 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\n",
"text/plain": [ "text/plain": [
"<Figure size 432x288 with 1 Axes>" "<Figure size 460.8x403.2 with 1 Axes>"
] ]
}, },
"metadata": {}, "metadata": {},
...@@ -99,7 +101,7 @@ ...@@ -99,7 +101,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 11, "execution_count": 110,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -111,14 +113,14 @@ ...@@ -111,14 +113,14 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 15, "execution_count": 111,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"image/png": 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\n", 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\n",
"text/plain": [ "text/plain": [
"<Figure size 432x288 with 1 Axes>" "<Figure size 460.8x403.2 with 1 Axes>"
] ]
}, },
"metadata": {}, "metadata": {},
...@@ -132,13 +134,6 @@ ...@@ -132,13 +134,6 @@
"plt.legend()\n", "plt.legend()\n",
"plt.show()" "plt.show()"
] ]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
} }
], ],
"metadata": { "metadata": {
......
9_gradient_descent.ipynb 0 → 100644
{
"cells": [
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from jupyterthemes import jtplot\n",
"jtplot.style(theme='gruvboxd')"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"N = 100\n",
"lr = 0.1\n",
"w = 20\n",
"R = []\n",
"W = []\n",
"for i in range(N):\n",
" w = w - 2*lr*w\n",
" W.append(w)\n",
" R.append(i)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[0.00000000e+00, 1.60000000e+01],\n",
" [1.00000000e+00, 1.28000000e+01],\n",
" [2.00000000e+00, 1.02400000e+01],\n",
" [3.00000000e+00, 8.19200000e+00],\n",
" [4.00000000e+00, 6.55360000e+00],\n",
" [5.00000000e+00, 5.24288000e+00],\n",
" [6.00000000e+00, 4.19430400e+00],\n",
" [7.00000000e+00, 3.35544320e+00],\n",
" [8.00000000e+00, 2.68435456e+00],\n",
" [9.00000000e+00, 2.14748365e+00],\n",
" [1.00000000e+01, 1.71798692e+00],\n",
" [1.10000000e+01, 1.37438953e+00],\n",
" [1.20000000e+01, 1.09951163e+00],\n",
" [1.30000000e+01, 8.79609302e-01],\n",
" [1.40000000e+01, 7.03687442e-01],\n",
" [1.50000000e+01, 5.62949953e-01],\n",
" [1.60000000e+01, 4.50359963e-01],\n",
" [1.70000000e+01, 3.60287970e-01],\n",
" [1.80000000e+01, 2.88230376e-01],\n",
" [1.90000000e+01, 2.30584301e-01],\n",
" [2.00000000e+01, 1.84467441e-01],\n",
" [2.10000000e+01, 1.47573953e-01],\n",
" [2.20000000e+01, 1.18059162e-01],\n",
" [2.30000000e+01, 9.44473297e-02],\n",
" [2.40000000e+01, 7.55578637e-02],\n",
" [2.50000000e+01, 6.04462910e-02],\n",
" [2.60000000e+01, 4.83570328e-02],\n",
" [2.70000000e+01, 3.86856262e-02],\n",
" [2.80000000e+01, 3.09485010e-02],\n",
" [2.90000000e+01, 2.47588008e-02],\n",
" [3.00000000e+01, 1.98070406e-02],\n",
" [3.10000000e+01, 1.58456325e-02],\n",
" [3.20000000e+01, 1.26765060e-02],\n",
" [3.30000000e+01, 1.01412048e-02],\n",
" [3.40000000e+01, 8.11296384e-03],\n",
" [3.50000000e+01, 6.49037107e-03],\n",
" [3.60000000e+01, 5.19229686e-03],\n",
" [3.70000000e+01, 4.15383749e-03],\n",
" [3.80000000e+01, 3.32306999e-03],\n",
" [3.90000000e+01, 2.65845599e-03],\n",
" [4.00000000e+01, 2.12676479e-03],\n",
" [4.10000000e+01, 1.70141183e-03],\n",
" [4.20000000e+01, 1.36112947e-03],\n",
" [4.30000000e+01, 1.08890357e-03],\n",
" [4.40000000e+01, 8.71122859e-04],\n",
" [4.50000000e+01, 6.96898287e-04],\n",
" [4.60000000e+01, 5.57518630e-04],\n",
" [4.70000000e+01, 4.46014904e-04],\n",
" [4.80000000e+01, 3.56811923e-04],\n",
" [4.90000000e+01, 2.85449539e-04],\n",
" [5.00000000e+01, 2.28359631e-04],\n",
" [5.10000000e+01, 1.82687705e-04],\n",
" [5.20000000e+01, 1.46150164e-04],\n",
" [5.30000000e+01, 1.16920131e-04],\n",
" [5.40000000e+01, 9.35361048e-05],\n",
" [5.50000000e+01, 7.48288838e-05],\n",
" [5.60000000e+01, 5.98631071e-05],\n",
" [5.70000000e+01, 4.78904857e-05],\n",
" [5.80000000e+01, 3.83123885e-05],\n",
" [5.90000000e+01, 3.06499108e-05],\n",
" [6.00000000e+01, 2.45199287e-05],\n",
" [6.10000000e+01, 1.96159429e-05],\n",
" [6.20000000e+01, 1.56927543e-05],\n",
" [6.30000000e+01, 1.25542035e-05],\n",
" [6.40000000e+01, 1.00433628e-05],\n",
" [6.50000000e+01, 8.03469022e-06],\n",
" [6.60000000e+01, 6.42775218e-06],\n",
" [6.70000000e+01, 5.14220174e-06],\n",
" [6.80000000e+01, 4.11376139e-06],\n",
" [6.90000000e+01, 3.29100911e-06],\n",
" [7.00000000e+01, 2.63280729e-06],\n",
" [7.10000000e+01, 2.10624583e-06],\n",
" [7.20000000e+01, 1.68499667e-06],\n",
" [7.30000000e+01, 1.34799733e-06],\n",
" [7.40000000e+01, 1.07839787e-06],\n",
" [7.50000000e+01, 8.62718293e-07],\n",
" [7.60000000e+01, 6.90174635e-07],\n",
" [7.70000000e+01, 5.52139708e-07],\n",
" [7.80000000e+01, 4.41711766e-07],\n",
" [7.90000000e+01, 3.53369413e-07],\n",
" [8.00000000e+01, 2.82695530e-07],\n",
" [8.10000000e+01, 2.26156424e-07],\n",
" [8.20000000e+01, 1.80925139e-07],\n",
" [8.30000000e+01, 1.44740112e-07],\n",
" [8.40000000e+01, 1.15792089e-07],\n",
" [8.50000000e+01, 9.26336714e-08],\n",
" [8.60000000e+01, 7.41069371e-08],\n",
" [8.70000000e+01, 5.92855497e-08],\n",
" [8.80000000e+01, 4.74284398e-08],\n",
" [8.90000000e+01, 3.79427518e-08],\n",
" [9.00000000e+01, 3.03542014e-08],\n",
" [9.10000000e+01, 2.42833612e-08],\n",
" [9.20000000e+01, 1.94266889e-08],\n",
" [9.30000000e+01, 1.55413511e-08],\n",
" [9.40000000e+01, 1.24330809e-08],\n",
" [9.50000000e+01, 9.94646473e-09],\n",
" [9.60000000e+01, 7.95717178e-09],\n",
" [9.70000000e+01, 6.36573743e-09],\n",
" [9.80000000e+01, 5.09258994e-09],\n",
" [9.90000000e+01, 4.07407195e-09]])"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"W = np.vstack([R, W]).T\n",
"W"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 460.8x403.2 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(W[:,0], W[:,1])\n",
"plt.show()"
]
}
],
"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": "3.6.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
9_gradient_descent2.ipynb 0 → 100644
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