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Exploring Depth, Width and Activation Functions for Neural Networks
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd \n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import tensorflow as tf\n",
"from sklearn.model_selection import train_test_split as tts"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question: \n",
"\n",
"# Can a very simple NN with 1 layer and 1 neuron fit a simple linear equation with a `linear` activation function?"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"x = np.linspace(0,10, 101)\n",
"y = 3*x + 2\n",
"\n",
"X_train, X_test, y_train, y_test = tts(x,y)\n",
"\n",
"plt.scatter(X_train,y_train)\n",
"plt.scatter(X_test, y_test)\n",
"plt.title('Original Data');"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(tf.keras.layers.Dense(1, activation = 'linear'))\n",
"model.compile(optimizer='adam',\n",
" loss='mse',\n",
" metrics=['mse'])\n",
"model.fit(X_train.reshape(-1,1), y_train, epochs = 1000, verbose = 0);"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(X_train, model.predict(X_train))\n",
"plt.scatter(X_test, model.predict(X_test))\n",
"plt.title('Predicted');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Answer: Yes.\n",
"\n",
"<hr>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Question:\n",
"# Can a very simple NN with 1 layer and 1 neuron fit a sinusoid with a linear activation function?\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"x = np.linspace(0,12, 101)\n",
"y = np.sin(x)\n",
"\n",
"X_train, X_test, y_train, y_test = tts(x,y)\n",
"\n",
"plt.scatter(X_train,y_train)\n",
"plt.scatter(X_test, y_test)\n",
"plt.title('Original Data');"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(tf.keras.layers.Dense(1, activation = 'linear'))\n",
"model.compile(optimizer='adam',\n",
" loss='mse',\n",
" metrics=['mse'])\n",
"model.fit(X_train.reshape(-1,1), y_train, epochs = 1000, verbose = 0);"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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gwQIeeeQRdu7cyezZs5k6dSqzZ88mJycHgI0bN3L11VcDlmIyP/jBD5g/fz6jR4/2iAShNxh3ojd3FXG2tYO756e4/d7fnzWSt3YX8/aeIr1VtQ+qqG/m3T0l3JSZTExY/7cx6Y+FY+MYHTuIFzYVcE1GgkfUFf5gbwmPvXeQJuuMppKaJh57z7K/z/VTnbt777Fjx1i3bh0mk4m6ujo2bdqEv78/69at4+c///kFm9QBHD16lA0bNlBfX096ejo//vGPCQgwbotv3SJwErNZ8dqOk8wYFcW4hMFuv//EpAgyRwzhb9tP6EU+PujVbYW0mc2GvAnw8xP+JWsUB0tq2XH8tNvv352n1uScSwKdmto6eGpNjtPvddNNN2EyWVZu19bWctNNNzFx4kQefPBBsrO731X/qquuIigoiJiYGOLi4igvL3d6XH2hE4GTbMqt5OTpRm6bOcKwGG6fPZKTpxvZeKzCsBg092tu6+AfX53kivFD+7zFtLN8a1oyUYMCeXFzgSH376q0pvuJEz0dd4Tt1tP//u//zoIFCzh06BAfffQRzc3dT+vuut30xcYX3EEnAif5x1cniAkL5MoJQw2L4cqJQ4kfHMQr204YFoPmfp8eKqO2qY3b3Tw2YCs4wMRtM0ew7kgFRacbDYujU2JkSJ+OO0ttbS1JSZaup1deecWl93ImpyQCEblSRHJEJE9EHu3m8YdEZJ/145CIdIhIlPWxQhE5aH3MO7YU7aL4TCPrj1ZwyyXDDa3eFGDy47uXjmDTsUoKKhsMi0Nzrzd2FjEyOpSZoy+sjOVOt1wyDBF4e7fxU0kfuiKdkC51P0ICLFtjuNLDDz/MY489xpw5c+jo8J4V1w5vQy0iJuAYsARLkfpdwK1KqcM9nH8N8KBSaqH1+0IgUylld7ULT9uG+qk1R3l2Yz6bH1lIkovfcfSmor6ZOSu+4LuXjuDxa42p4qS5T0FlAwv/+CUPX5nulgWMvbn95Z0cK69nyyMLMfk5d9C4r9tQf7C3hKfW5FBa00RiZAgPXZHu9IFiT9aXbaidMWtoBpCnlCqw3ugN4Dqg20QA3Aq87oT7eoSW9g7e3FXEonHxhicBgLjwYK6cmMD7e0t4bNlYgvyds/2w5pne3F2EyU/49vRko0MB4ObMYdzzz6/ZnFvJ/PQ4Q2O5fmqST/3hd4Qz+jGSANu2YLH12AVEJBS4ErCdT6WAtSKyR0SW93QTEVkuIrtFZHdlpefsg77ucAVVDa2GDhJ39e3pydQ2tbHhqB40Hsha2828u6eYRWPjiAsPNjocABaPj2NIaABveUD3kGY/ZySC7tp/PfU3XQNsVUrZzjGbo5SaBiwF7hGRed1dqJRaqZTKVEplxsbGOhaxE72/t5j4wUFkeVAx+azUGOLCg3hnj94ieCD74mg5VQ2tbttOwh5B/iZumJrM54fLqW7Q26N7C2ckgmLA9icxGSjt4dxb6NItpJQqtX6uAN7H0tXkFU6fbWVjTiXXT0lyen+oI0x+wg1Tk9iYU6F/GQewN3YVMXRwMJeNMbYLpqvvXDKMtg6laxV4EWckgl1AmoiMEpFALH/sV3U9SUQigMuAD22ODRKR8M6vgcuBQ06IyS0+PlBKu1l5ZD/kjdOSaTcrVu3vKSdr3qy8rpkvj1VyU2ayR70JAUgfGs7kYZG8tbsIb6yJ7oscTgRKqXbgXmANcAR4SymVLSJ3ichdNqfeAKxVSp21ORYPbBGR/cBO4BOl1GeOxuQu7+8tYezQcENWEvcmfWg4ExIH897X+l3ZQPTJgTKUguumeN6bEICbM5M5Vt5Admmd0aFodnDKXkNKqdXA6i7Hnuvy/SvAK12OFQCTnRGDux2vOsvekzU8ttT5pQCd5VvTkvn1x4c5Vl7PmPhwo8PRnGjV/lLGJwx26+aGfbFsYgL/8WE2Hx0oZWJShNHhOEV1dTWLFi0C4NSpU5hMJjrHK3fu3NlrMfqNGzcSGBjI7NmzXR5rX+mVxf30wd4SRODaKYlGh9Kja6ck4u8nvPt1sdGhaE50srqRfUU1Hv2zN2RQIFlpMXy8v2zAdA/1tg11bzZu3Mi2bdvcEGnf6UTQD0opPthXwqzR0SREGL92oCcxYUFcNiaWVftK9UZ0A8hHByzjPtdM9txEAJa6xiU1TewtqjEmgANvwdMT4fFIy+cDbzn9Fnv27OGyyy5j+vTpXHHFFZSVlQHwpz/9ifHjx5ORkcEtt9xCYWEhzz33HE8//TRTpkxh8+bNTo/FEXob6n74+mQNJ6obudeNxWf666qMBNYfrWBfcQ3Thg8xOhzNCT7aX0rmiCEesYDxYpZMiCfwfT8+2l/q/p+9A2/BR/dDm3WTudoiy/cAGTc75RZKKe677z4+/PBDYmNjefPNN/nFL37Byy+/zIoVKzh+/DhBQUHU1NQQGRnJXXfdRVhYGD/72c+ccn9n0i2Cflh9sIxAkx9XTDRugzl7LR4fT4BJWH2gzOhQNCc4Vl7P0VP1Ht8aABgcHMCC9Fg+OVBGh7tbpOt//U0S6NTWZDnuJC0tLRw6dIglS5YwZcoUfvOb31BcbOmGzcjI4Lvf/S7/+Mc/8Pf3/PfbOhH0kVKKzw6dIistxuXFwZ1hcHAAc9Ni+fTQqQHTV+vLVu0rxU9g2aQEo0Oxy9UZiVTUt7DT3XUKansYF+vpeD8opZgwYcK5cYKDBw+ydu1aAD755BPuuece9uzZw/Tp0w3fZro3OhH00cGSWkpqmrjSC1oDnZZNSqCkpon9xbVGh6I5QCnFRwdKmZMaQ2y4e6uQ9deicXGEBJj4+ICb17NE9LD3Uk/H+yEoKIjKykq2b98OQFtbG9nZ2ZjNZoqKiliwYAFPPvkkNTU1NDQ0EB4eTn19vdPu70w6EfTRp4dOYfITloyLNzoUuy0ZZ+0eOqi7h7zZ4bI6TlQ3cpWXtAYAQgP9WTw+ntUHy2hzZ3H7Rb+CgC5jKAEhluNO4ufnxzvvvMMjjzzC5MmTmTJlCtu2baOjo4PbbruNSZMmMXXqVB588EEiIyO55ppreP/99/VgsbdTSvHpwTJmp0QzZFDv08U8RURoAHNSY1h9sIzHlo71iJqyWt+tyS7HT2DJeO95EwJw1aQEPtpfyq7jp5ntrj25OgeE1//a0h0UkWxJAk4aKH788cfPfb1p06YLHt+yZcsFx8aMGcOBAweccn9n04mgD46eqqewupEfzfO+4vDLJiXw8DsHOFhSS0ZypNHhaP2wNvsUmSOjiHZzcXpHXTYmluAAP9YeLndfIgDLH30n/eEf6HTXUB98eugUInD5eO8ZH+h0+fh4/P2ET3T3kFc6UX2Wo6fqudzLWgMAIYEmslJjWZutJyx4Kp0I+uCzQ2VcMjLKawbqbEWGBjI7NYbP9Owhr7Q2uxyAKwysie2IyyfEU1rb7PDeQ/pn1z59/XfSicBO+ZUNHCtvYJkXzRbq6vLx8ZyobiRf1zP2OmsPn2JcwmCGRYUaHUq/LBobh59Yurf6Kzg4mOrqap0MeqGUorq6muBg+4sV6TECO517R+bFiWDRuDh++QF8friC1Di9CZ23qKxvYfeJMzywKM3oUPotOiyIzJFRrD1czr9d3r8C8snJyRQXF+NJFQo9VXBwMMnJ9k+V1YnATuuPlDMxabBH7y3Um4SIECYmDWbdkXJ+PD/F6HA0O607Uo5S3jk2Zevy8fH85pMjnKxuZHh031s2AQEBjBo1ygWRabpryA6nz7by9ckzLBzrfQN1XS0eF8/XJ8/oymVeZG32KYZFhTAuwbtbcZ2JbO3h/ncPaa6hE4EdNuZUYFaweJxnlQTsj8Xj4lEKvtCF7b1CQ0s7W/OquXz8UK9f/zE8OpSxQ8NZe7jc6FC0LpySCETkShHJEZE8EXm0m8fni0itiOyzfvzK3mud5YO9JcxZ8QWjHv2EOSu+4IM+1FNdf6SC2PAgJiZ6f4GNCYmDSYgIZv0RnQi8wZbcKlo7zCz2opXsF3P5hKHsLjytW6QexuFEICIm4C/AUmA8cKuIjO/m1M1KqSnWj1/38VqHfLC3hMfeO0hJTRMKKKlp4sE39zHSjqTQ2m5m07FKy6wHD6sN2x8iwqJxcWzKraS5rcPocLRebDhaQXiwP5kjB8YW4ovHxWFW8OUxPeDrSZzRIpgB5CmlCpRSrcAbwHVuuNZuT63JoanLH73OCWi9JYVdhaepb2ln0QB5RwawaFw8ja0dbC+oNjoU7SKUUmzIqWBeWiwBpoHRizsxMYKYsCA25OhE4Emc8dOVBBTZfF9sPdbVLBHZLyKfisiEPl6LiCwXkd0isruv08dKa5ou+vjFksK6I+UE+vsxJzW6T/f0ZLNGRxMaaGL9Ed1X68myS+uoqG9hwVjvH5vq5OcnzE+PZdOxStrduQmddlHOSATd9Zd0XfHxNTBCKTUZ+D/ggz5cazmo1EqlVKZSKrOzYLS9EvtQyck2KfzkzX38dWshZrPq9/iCJwoOMDEvLZb1Ryr04hwPtsE6oH/ZmL79vHu6Belx1Da1sc+oEpbaBZyRCIqBYTbfJwPnbT6ulKpTSjVYv14NBIhIjD3XOsNDV6QTEmDq9/XtZsWZxrY+jy94sgVjYymrbeZYuV5l7Km+yKlgcnKEV25pcjFZaTGY/ETPXPMgzkgEu4A0ERklIoHALcAq2xNEZKhY576JyAzrfavtudYZrp+axO9unHSuxqujQ76d76Gn133OJR/MQ7mwOLarzLO+y9yYo38ZPVF1Qwv7imoGVLdQp4iQAKaPGKLHCTyIwyuLlVLtInIvsAYwAS8rpbJF5C7r488B3wZ+LCLtQBNwi7L0SXR7raMxdef6qUlcP9Uy/PDB3hKeWpNDSU0TQg99Ub241m8LKwJeJFRaLQdqi2j/8D5+syqbVxtmkBgZwkNXpJ+7p6dJiAhh7NBwvjxWyb9eplcZe5pNuZUoBQsHYCIAy+ta8elRTtU2MzTC/j1xNNdwylQEpdRqpdQYpVSKUuq31mPPWZMASqk/K6UmKKUmK6VmKqW2XexaV7t+ahJbH11I4YqrePo7U/rVUnjY/61vkoCVf0czP2z9BwrvaC1clh7LrsLTNLR4dj1VX/TF0UpiwgbG2pXuLEi3JDjdIvUMA2NOmgN6Sgq9SZSqHo5Xn2stJEkVgoLaIpreu5cHfv6YR40rXDYmlrYOxba87l+LZoz2DjNf5lQwPz12QKxd6c6Y+DASI4L1OIGH8PlEYMs2KWSlxpxrIUSGBDAkNAD4ptVQqrqvtFSqorttLYTQwkP+b3nUYHPmiCgGBZr04h4Ps6+ohrrm9nPvmgciEWH+2Di25lXR0q4XNhpNJ4IeFJ1pZOHYOApXXMW+/7icvb+6/LxWw1PtN9PE+bM5GlUgT7bffNHWAnjOYLNlfUQMG3Mq9TRSD7LpWCV+AlnuLOtogAXpcZxt7WBP4RmjQ/F5OhF0o7DqLCeqG7ks/cL5252thv994neE3PhniBgGCI0hCfxKLWeVOeuirYVOntJ9dFl6LCU1TbpYjQfZlFvFlGGRRFhboQPVrJRo/P2ETbm6a9Jouh5BNzq7SnpdyGNTHDsUyNpbwvY1OTxVdzMrAl8ihG821upsLXS6WPfRk3VwyQc/Qn1YTVPIUJ5s+47LZiLNPzdoV6mL1XiAmsZWDhTXcN9C7y1CY6+wIH+mjxjC5txKHl061uhwfJpuEXTjy2OVjIwOZUT0oD5d111rQSGUqBgebfshq8xZ587tqfsoSarOaymENpXxcNszXOO3xSXjC0mRIaTFhelxAg+xJa8Ks/pmncdAN29MLNmldVTW691IjaQTQRfNbR1sz692fFl/xs3w4CHk8Rp2Xb+JPYOXAL0PNnfgd0FLIVRaedjfMn5g72Z5fXHZmFh2FJymqVUP2hlt07FKwoP9mZw8MKeNdjU3zfJ7sFXPXDOUTgRd7C48Q1NbR7fjA/3V3RTVngab/eh+I67OgWZbzkoKc8fE0tphZmfh6T5dpzmXUorNuVVkpcbgP0B2G+3NxMQIhoQGsClXt0iN5Bs/bX2wKbeSAJMwc7RrdhvtrfvInoHm7jiSFGaMjCLQ5McW/ctoqLyKBspqm32mWwgsu5FmpcWyObdKz1wzkE4EXWzOrWL6iCGEBrphHL2b7qOLTUu1V1+TQkigicyRQ9isZ28YqnOcprO7xFfMS4uhsr6Fo6fqjQ7FZ+lEYKOqoYUjZXXMTXP/O7KLTUt9MuBuVpmz+rVZnr1JISsthqOn6qmob3b0pWj9tDm3itGxg0geEmp0KG7V+fu2WbdIDaOnj9roHLCaY/RCni7TUh+3fji6WV7XpPCTN/eRZJ2SOi8tlic/y2FrXhU3TE120gvR7NXc1sGO49Xccslwo0Nxu6ERwYyJD2NzbhXL5+kNEI2gWwQ2tuRWERESwKQkz5yx4YzN8jp1Xd08buVIoqSeze+vBA/eKG+g2nPiDM1tZp/rFuo0Ly2WHcf1zDWj6ERgpZRiS14Vs1OiMXnBRl/OSAq2q5tNYma2HGJL6xjLoJ2HbpQ3UG3Jq8LfT7jURZMUPN3cMbG0tuuZa0bRicCqoOosZbXNZHnhO7L+JoWuq5vn+R2ggiEcU5auIU/cKG+g2ppXxdThkYQF+WZvbefMNb0TrjGckghE5EoRyRGRPBF5tJvHvysiB6wf20Rkss1jhSJyUET2ichuZ8TTH1usM2bmpnr31L2+JIWuq5uzTAcB2GyeZHOOZ22UNxDVNLZysKTW+LEpA4UEmpg2IpItOhEYwuFEICIm4C/AUmA8cKuIjO9y2nHgMqVUBvBfwMoujy9QSk1RSmU6Gk9/bc6tYlhUCMOjB86Mjd6SQtc1C4lymtFSel4i8MSN8gaa7fnVKDXwdxvtTVZqDNmldZw+29r7yZpTOaNFMAPIU0oVKKVagTeA62xPUEptU0p17jX7FZYi9R6jrcPMVwXVZHl5a+Bi7F3dPNfvIDvM42hR/n3aKE93H/XflrwqBgWamDws0uhQDDXbmgi351+4il5zLWckgiSgyOb7YuuxnvwL8KnN9wpYKyJ7RGR5TxeJyHIR2S0iuysrnTvf+EBxDQ0t7T4zY6OnNQuERDEnuJBmgvjcnGn3Rnldu490UuibrXlVzBwdTYCPbCvRk4ykCMKD/HX3kAGcMTLVXfdzt1PcRWQBlkSQZXN4jlKqVETigM9F5KhSatMFT6jUSqxdSpmZmU5di745twoRmJ3igzM2bNYsAFza1Ibfr9eyKu23ZJfWgc2ahVIVQ3I3yaC77S9sk8KW95/h8rXvEtp0CiKSYdGvzrunLys63UhhdSPfnzXS6FAM52/yY2ZKtN6AzgDOSATFwDCb75OB0q4niUgG8CKwVCl1ru2nlCq1fq4QkfexdDVdkAhcaVteNRMTI4gMDXTnbT1SREgAk5IjqT7bytZHFwLfLGSzp85CV9f6beHX8iKhTdYuJeu4wqNv7GVT8AKUgtqmNpfUWvAG2/Itf/S8cbaaK8xJiebzw+UUnW5kWNTAGa/zdM5oi+4C0kRklIgEArcAq2xPEJHhwHvA95RSx2yODxKR8M6vgcuBQ06IyW6Nre3sLTrD7FQfbA30YE5KNPuLLN1l0Lc6C11dbFzhTGMbNU1tKHy3O2lrXjWx4UGkxYUZHYpHyNLbUhvC4USglGoH7gXWAEeAt5RS2SJyl4jcZT3tV0A08EyXaaLxwBYR2Q/sBD5RSn3maEx9savwDG0dijkp+h1ZpzmpMbSbFTuPdzNo10udha56G1ew5WtjDGazYmueZdtpEc9fxOgOKbFhxIUH6XECN3PK6hWl1GpgdZdjz9l8/UPgh91cVwBM7nrcnbblVRFgEi4ZGWVkGB5l+oghBPr7sTWvmoVj43s87/qpSee6cnraB6kv4wq2zl+3YCnbKQNsfCGnvJ7qs62+OTbVAxEhKzWGjccqMZsVfl6wyn8g8O1pCsDW/CqmDh9CSKDJ6FA8RnCAicwRQ/rUPO9ueqoALwbeRrsp+Lxz7d1We6CvW/CYTQ49zJzUGE6fbeXIqTqjQ/EZvrme3aqmsZXs0jp+smiM0aF4nDmpMTy1JoeqhhZiwoJ6v8CGbUsBroIDE2D9r1G1xZSqaH7fdvNFxxU6XWx8Iasm64IdVL1toHl7fjWjYgaRaF3op1nMsVlPMCHRMzeAHGh8ukXQuaJzjh4ovkBnd4VTFvd0M64gwJDQACJDAgD7tsD45rj3r1to7zCz4/hp3S3UjaERwYyOGcQ2vbDMbXy6RbA1X6/o7Mkk6+KebflVXDM50WnPe35r4RvdjTH0d92CN7QUDpTU0tDSzmw9SaFbs1Ki+WBvCW0dZp9faOcOPp0ItuVVM2NUlP5B64a/yY9LR0ezNc8978q6G3juz7oF6GGgOWSI5WDTGY9Y1NbZ0po5Wk9S6M6c1Bhe23GSA8W1TB8xxOhwBjyfTQRltU0UVJ3l1hm+VxHKXnNSo1l3xP2Le75JCgvhwNR+jS90DjSfG2Nostnn3mZR2+7BSwxpNWzNq2JcwmCi+zj+4itmju7smqzSicANfPat8DbrO129kKxnnd0W2wsM7Kvt47qFTt0NNNvqHHQ2Ylvt5rYOdp84o8cHLiJqUCDjEgbrcQI38d1EkF/NkNAAxg0dbHQoHmtMfBjRgwI9ZjdIR2otdCdRqi6Ynsp7y+HxCJcmha9PnKG13awTQS9mp0Sz+8QZmtt0+UpX88lEoJRie34Vs1Ki9YKVixARZqVEsy2/ylK+0oP0tdZCd8z4ddNqsL5OF65Z2JZfjclPmDFKjw9czJzUaFrbzXx94kzvJ2sO8clEcKK6kdLaZmbpGRu9mp0SQ3ldCwVVZ40OpUf21lqw1agCMWG+6PO6qtbCtvwqMpIjCA8OcOh5BrpLRkZh8hPdPeQGPpkIOn+wdNO8d53/Rt7yy3ixWguERJ23WV6JHa0GZ69ZqG9uY39xrd7byg7hwQFkJEec26FVcx2fnDW0Lb+K+MFBjI4ZZHQoHm9EdCiJEcF8lV/N92aOMDqcvulSawEsXUe79pawZ00OT9VxwfTUrpy9ZmFX4Wk6zIpZ+k2IXWanRPPclwU0tLQTFuSTf67cwudaBEopviqoZnaK3vHRHpZxghi2F1RjNnvWOEF/dd9qgK7Dzn1Zs2BvS2FbXjWB/n56SqSd5qTE0NHTTria0/hcis2taKCqoZVZo/U7MnvNTonm3a+LySmvZ1zCAJtlZdtqOPBWv9YsdOqupXBH2E4eDnjzXHW27a1PMG14LMEBepNDe0wbMYRAkx/b8y++E67mGJ9rEWyz7viom+b2m+Vl4wT91s81C91RWBa1Pdz2DKFNZYDiTM0ZDp8Rao7v9Zo9kYwWHGBi2ojIgf+zZzDfSwT51QyLCtFl8PogMTKEUTGD2O5Dg3Z9WbPQk66L2naYx6Hw437Te+dqOTf+fiy4cTGbN5qdEsPhsjpqGnteIKg5ximJQESuFJEcEckTkUe7eVxE5E/Wxw+IyDR7r3WmDrN1fGC0nrHRV7NSotlRcJr2jotPuRyI+psUui5q224eTyjNLPTba63lvPJca8Fdi9m80eyUaJSCrwpO936y1i8OJwIRMQF/AZYC44FbRWR8l9OWAmnWj+XAs3241mmOlNVR19yut5Xoh9kp0dS3tHOo1LeLhfQlKXRd1LbNPIFMvxyqiOxhC4xvFrPppPCNjORIQgNNPtUidTdntAhmAHlKqQKlVCvwBnBdl3OuA/6mLL4CIkUkwc5rnaZzPrIeKO67zk3A9Jzub/SWFJ5sv5lGFQhAhYogVyVziRzlyfab7dgCw/UrnL1FoL8fmSOj9DiBCzkjESQBRTbfF1uP2XOOPdcCICLLRWS3iOyurKzsV6BnWzqYPCySuMHBvZ+snScmLIj0+HCP2XfI03SXFD4yZ/FkwN00hiSw3TwBgF3mdFaZs+zaAqOTq1Y4e5PZKdHkVjRQUd9sdCgDkjOmj3bXKu464bync+y51nJQqZXASoDMzMx+TWh/cMkYfrI4rT+XaljGCd7YdZLWdjOB/j43z8BuF5Tq5D/56r0DBO8tIS90JlLbzIuBt/FL9Rz+Hfb9YetphbOnF+Bxls4V7l8VnOZaJxZK0iyckQiKgWE23ycDpXaeE2jHtU6lF5H13+yUaF7ZVsi+ohq9YVofbcuvJis1lhdvz7Qe+aaWM7VFcK4uW/fsXeEcGRKACNQ0tpE4gBLEhMQIwoP92Z5fpROBCzjjbd0uIE1ERolIIHALsKrLOauA71tnD80EapVSZXZeq3mIS0dH4yd6nKCvSmqaOFHdeOHeVtZ1CzxeCzeudMoK55qmNs40tqHwzlrOPTH5CTNHR+txAhdxOBEopdqBe4E1wBHgLaVUtojcJSJ3WU9bDRQAecALwN0Xu9bRmDTXiAgJYEJihP5l7KPOcZWLLmLsJinYbpDXlxXOtpy1WZ4nmDU6mhPVjZTUNBkdyoDjlC0mlFKrsfyxtz32nM3XCrjH3ms1zzU7JZqXtx6nqbWDkEC9TYI9tuVXET0okPT4cPsusG57YbtBHjVNvXQe9a7bWs4eUL/ZXp3TvrflVXFT5rBeztb6Qo/4aX0yKyWatg7F7hN6cY89lFJsy6tmZj+LIDljhbOtzlrOtlXZvGV66pi4cEvFPCNLpw5QOhFofXLJyCj8/URPI7XT8aqznKprdkrtC1dsewHeMz3Vz0+YmRLN9vxqj6uY5+10ItD6ZFCQP5OH6U3A7PVNESTnbmvSXVIQIDIkgCGhlspnfanl7OwCPK4yJyWGstpmjntwxTxv5HPbUGuOm50SzV825FHX3MZgXW7xorbnV5MQEczIaNdtcnj+uoVvfLC3hKfW5FBiM75QqmJI7iYZOLsAj6vYVswbHRtmSAwDkW4RaH02KyUas4KdehOwizKbFdsLqpmVEm3I+hV7azn3twDP47/5D7fvntpZMU93TTqXbhFofTZt+BCC/P3Yll/N4vG6WEhPcsrrOX221endQv3xTathIRyY6nABHkuthRcJbbeON1gHnR99Yy+7By9xWauhs2LehpwKzGbVrwF47UK6RaD1WXCAicyRQ/TCsl5ss2f9gBGcUIDHyEHn2SnRnD7bSk55vVOf15fpRKD1y+yUGI6eqqeqoefC775ue34VI6NDz83u8UTOqrXwzXHXDzr7TMU8N9KJQOuXzkE73VfbvfYOMzsKTjPLA7qF7OVIrYVvjvc+6OxoUvDFinmuphOB1i+TkiIID/LX3UM9OFRaR31Lu1PWDxihL7UWOvVl0Nmyunkeqp8Dzb5cMc8VdCLQ+sXf5Melo3WxkJ5szbMkyJkDoAhSb7UW+ronkjNWN89JiaG+pZ2DJbXOeIk+T88a0vptdkoM645UUHymkeQhrpsn74225Vcxdmg4seFBvZ/sRbqrtQB92xPpYgPNWTVZPPTOfh5flU1tU89bac8cbdkGfVt+NVOHD3HOi/NhOhFo/XZuE7D8am7O1ImgU3NbB7sKz/C9mSOMDsVtbBNEdwvZbPU20NzWoahpagPO3yCvKWQoT7Z9h1cbZpAYGUJiZDBb86q4Z0Gqq16Wz9BdQ1q/pcdbNgHblqfHCWztOXGG1nYzc1K9v1uoP3obX7B3oLlrF1JoUxkPtz3DNX5bKKlporSmmW351cz+3XqP2QLDW+lEoPWbZXGPpViI3gTsG1vyqvD3E2aM8s1EYMuR1c3ddSGFSisP+58/sDyibpdDA8+a7hrSHDQnNYaPD5SRV9FAmr377Q9w2/KqmDIskrAg/etlq6+rm3vrQgIQzEzwO0lS57luWuE80DjUIhCRKBH5XERyrZ8vGLURkWEiskFEjohItog8YPPY4yJSIiL7rB/LHIlHc7+sVEszf6vuHgKgtrGNgyW1zEn1nvUDhuhmdbMAQ0IDCLBuG2FPF1KGFLDTPPa8x71lW21P4mjX0KPAeqVUGrDe+n1X7cBPlVLjgJnAPSIy3ubxp5VSU6wfulKZlxkWFcrwqFC26EQAwPaCaswKnQj6oLP76PiKq9j7q8t56qbJdnchLfDby0E1iho16LzzvGVbbU/haCK4DnjV+vWrwPVdT1BKlSmlvrZ+XY+lNrFuqw0gWWkxfFVwmja9uIdt+VWEBJiYMizS6FC8Vmdi+N8nfkfIjX+GiGGA0BiSwJMBd7PKnHVu4HmMFKPwY7t5/HnP4Y4VzgOJo52Y8UqpMrD8wReRuIudLCIjganADpvD94rI94HdWFoOZ3q4djmwHGD48OEOhq05U1ZqDP/ccZIDxTVMHxFldDiG2pJXxaWjowj01/MwnMJavxkgFHjc+tE5RfXT2hmE0sRW80SWmnYB/dtW2xNqLRip159WEVknIoe6+biuLzcSkTDgXeAnSqk66+FngRRgClAG/LGn65VSK5VSmUqpzNjY2L7cWnOx2SnRiMCWXN9eZXyqtpmCyrPM8aL9hbxVZ6vh/373BDMTA9jKlD6vcO6kWwp2tAiUUot7ekxEykUkwdoaSAAqejgvAEsSeE0p9Z7Nc5fbnPMC8HFfgtc8Q2RoIJOSItiSV8kDi9OMDscwneMks310/YBR5kzL4IuPD1P6UBm7jp+2e4Vzd7prKdwRtpOHA94ktOkURCTDol+da6UMFI62X1cBt1u/vh34sOsJYinN9BJwRCn1310eS7D59gbgkIPxaAaZkxrD3pM1NLS0Gx2KYbbkVhITFsi4oYONDsWndC7c25pb1e9ttbvzTQGeZwhtKrMc6ce+SN7A0USwAlgiIrnAEuv3iEiiiHTOAJoDfA9Y2M000SdF5KCIHAAWAA86GI9mkLmpMbSbFTuP+2b3kNms2JJXRVZqjK6a5Wbp8ZY9nTZ3mbnmjKRgZAEed3JosFgpVQ0s6uZ4KbDM+vUWevi3V0p9z5H7a55j2ghL+crNuVUsHOt75SstRXpayUrT41fuJiLMTb14+cq+7IVkq68FeLx10FlPbdCcIjjAxIxRUT67sGxzbiUAc9P0QLER5o6J4UxjG9mldb2e6y0FeNxJJwLNabJSYzhW3kB5XbPRobjd5twq0uPDiR8cbHQoPikr1dIS22RNyPby9AI87qITgeY0WdZ3w5tzfatV0NzWwc7C07o1YKDY8CDGJww+1zLrD08swOMuelcszWnGDR1MTFgQm45V8u3pyUaH4zY7j5+mtd3M3DF6fMBIc8fE8PKW45xtaWeQgxv+uboAz5N1nKuzIB4wJVUnAs1p/PyEeWNi2HC0gg6zwuQjs2c251YSaPJjxkjfXlVttHlpsTz/ZQE7jle7bMKCcwrwVLEi4MVvkkRtEby3HN77kWUbDZviO+4adNZdQ5pTXTYmljONbRzyoVqym3OruGTUEEICTUaH4tOmjxhCcIAfm465p2uyvwV4zPhd0FLoTCNdi++4a9BZJwLNqbJSYxCBTcf631frTSrqmjl6qp65etqo4YIDTFw6KrrPA8bO0JcCPCYuvjmjbfEd25lID729n6m/XssoFyQGnQg0p4oOC2JSUgRf+kgi6NxWQg8Ue4a5aTEUVJ6l+EyjYTF0t3uq7UBzSQ8tBVu2xXc6tZkVZxrbUFgSw2PvHXRaMtCJQHO6eWmx7C2qoa65zehQXG5jTiUxYUF6WwkPMc86YO8xM9e6KcDTXUuhq+7WKXTV1NbBU2tynBKmTgSa080bE0uHWQ34ovYdZsWm3EouGxOrt5XwEGlxYSREBPNljue1SLuvswBdl7LZs06hU2lNk1Ni04lAc7qpwyMJD/If8N1D+4pqqGlsY8FYPT7gKUSE+emxbMmrorXdgwslWVsKPF4LN668aPGdi0m0DlA7Sk8f1ZwuwOTH7NRoNh2rQimFZQPagWdjTgV+AnNTdSLwJPPT43h9ZxF7TpxhVooXbAneS/Gd0pomIkICONvaTlvHN5NUQwJMPHRFulNC0IlAc4l5Y2JZk11OfmUDqXHhRofjEhtzKpk+YggRoQFGh6LZmJMaQ4BJ2JhT4R2JoAfnL2o7PzE4e42BTgSaS8xPt1Qt3XC0ckAmgor6Zg6W1DrtHZnmPGFB/swYFcWGnAoeWzbO6HCcpmticCY9RqC5RFJkCGOHhrP+aHnvJ3uhzkVL89N1t5AnWpAex7HyBkOnkXoThxKBiESJyOcikmv9PKSH8wqtBWj2icjuvl6veaeFY+PYVXiG2qaBN410Q04FcdaNzjTP09ki3eiBs4c8kaMtgkeB9UqpNGC99fueLFBKTVFKZfbzes3LLBoXR4dZObQjpCdq7zCz+Vgl89NjB+xAuLdLiR3EsKgQNuZ0W0Zd68LRRHAd8Kr161eB6918vebBpgwbwpDQAL44MrB+GS2L5drPvevUPI+IsCA9jq151TS3dRgdjsdzNBHEK6XKAKyfe/rNUMBaEdkjIsv7cb3mhUx+wvz0ODbkWHYjHSi+OFqByU+Yk6q3lfBkC9LjaGrrYOfx00aH4vF6TQQisk5EDnXzcV0f7jNHKTUNWArcIyLz+hqoiCwXkd0isruycmB1NQxkC8fGcaaxjX1FNUaH4jTrDpdz6agoIkL0tFFPNnN0NEH+fnxxdGC1SF2h10SglFqslJrYzceHQLmIJABYP3f7L24tZo9SqgJ4H5hhfciu663XrlRKZSqlMmNj9UwNbzFvTCwmP+GLATJ7qLDqLLkVDSwZ75r97jXnCQk0kZUaw+eHy1Fq4LRIXcHRrqFVwO3Wr28HPux6gogMEpHwzq+By4FD9l6vebeIkAAyRwxh/QAZJ/j8sCWhLR6nE4E3uHxCPCU1TRwpqzc6FIfVNLbywBt7OVJW5/TndjQRrACWiEgusMT6PSKSKCKrrefEA1tEZD+wE/hEKfXZxa7XBpaFY+M4eqreaRtkGenzw+WMHRrOsKhQo0PR7LBwbDwisPbwKaNDcdj6IxV8uK/UJXsoOZQIlFLVSqlFSqk06+fT1uOlSqll1q8LlFKTrR8TlFK/7e16bWBZZH33vO6Id3cPnT7byu4Tp7lcdwt5jdjwIKYPH3KuJefNPss+RUJEMBnJEU5/br2yWHO51LgwUuPC+OyQd78r++JoBWYFi3Ui8CpLxseTXVrn1auMG1vb2XSsksvHx7tk7YpOBJpbXDlhKDuOn+b02a61Wr3H54dPMXRwMJOSnP+OTHOdzoH9dV7cKth0rJKWdjNXTBjqkufXiUBziysmDKXDrLy2e6i5rYNNx6pYPD5Oryb2MqNjLS3Sz730Zw9gTXY5kaEBzBgV5ZLn14lAc4uJSYNJigxhjZd2D23Lr6KprUPPFvJSS8bH81XBaWobvW/fq7YOM+uPlLNobDz+Jtf8ydaJQHMLEeGKCUPZnFtFQ0u70eH02ZpD5YQF+Xv1/va+7PLx8XSYFRu8cO+hrwqqqWtu54oJrnsTohOB5jZXThxKa4fZ6zYCa+sw81n2KRaPiyPI32R0OFo/TE6OJC48iE8PlRkdSp+tyT5FSICJeWNct5BWJwLNbaaPGEJMWKDXzR7amldFbVMbV2ckGh2K1k9+fsKySQlsyKmkvtl7uofMZsXa7HLmp8cSHOC6NyE6EWhuY/ITlowfyoajFV61I+THB8oID/Jn7hi9yZw3uzojgdZ2s1dNWNhbVENFfYvLZgt10olAc6srJw7lbGsHm3OrjA7FLq3tZtZkn2LJhHjdLeTlpg0fQkJEMB/v957uoY/2lxLo78eica7dmFknAs2tZqdEMyQ0gFX7S40OxS5b8iqpb27n6owEo0PRHOTnJ1w1KYFNuZVeMXuovcPMxwfKWDQ2jvBg1+50qxOB5lYBJj+uykjg88OnvGL20McHyggP9icrVe94OxBcPTmRtg7FGi/Ye2h7QTVVDS1cO9n1Y1M6EWhud92UJJrbzHzu4b+MLe0dfJ5dzhUThhLor39VBoLJyREMiwrh4wOe3z20al8p4UH+LBjr+npd+qdbc7vpw4eQFBnCh/s8u3to87Eq6lvauUp3Cw0YIsLVGYlszavy6O1Omts6+OzQKS6fMNSls4U66USguZ2fn3DtlEQ251ZR1dBidDg9+nB/KZGhAWTpkpQDytUZCXSYlUdPY96YU0l9SzvXTXHPlGWdCDRDXD8liQ6zYvVBz2yi1za2sSb7FNdOTiTARcv6NWOMTxjM6NhBfLC3xOhQerRqfwkxYYHMdtNKdv0TrhkifWg4Y4eGe+wv40cHLAVAbpo+zOhQNCcTEb49PZmdhac5XnXW6HAuUN/cxvojFVw1KcFlewt15dBdRCRKRD4XkVzr5yHdnJMuIvtsPupE5CfWxx4XkRKbx5Y5Eo/mXa6bksTXJ2s4We15+8S/vaeY9PhwJiYNNjoUzQW+NS0ZP4F39hQZHcoFPj14ipZ2M9e6qVsIHG8RPAqsV0qlAeut359HKZWjlJqilJoCTAcasRSw7/R05+NKqdVdr9cGrmunJCIC73xdbHQo58ktr2d/UQ03ZSbrLacHqPjBwcxPj+OdPcV0mD2rsP3ru06SGhfGtOEXvK92GUcTwXXAq9avXwWu7+X8RUC+UuqEg/fVBoCkyBDmpcXy5q6TtHc4vw5rf72zpxh/P+H6qUlGh6K50M2ZyZTXtbApt9LoUM45eqqOvSdruOWSYW59E+JoIohXSpUBWD/3NuH1FuD1LsfuFZEDIvJyd11LnURkuYjsFpHdlZWe8x+nOeb/XTqc8roWvjjqGTuStneYeW9vCfPT44gJCzI6HM2FFo6NJ2pQIG/v9pzuoTd2FhFo8uPGacluvW+viUBE1onIoW4+ruvLjUQkELgWeNvm8LNACjAFKAP+2NP1SqmVSqlMpVRmbKxe5TlQLBobR/zgIP6586TRoQCwKbeSyvoWbsp07y+i5n6B/n7cMDWJzw+Xe8Sagua2Dt77upgrJw4lalCgW+/dayJQSi1WSk3s5uNDoFxEEgCsny/2tm4p8LVS6tzWf0qpcqVUh1LKDLwAzHDs5Wjext/kx3cyh/HlsUqKThs/aPzPHUVEDwpkQbrrV3Nqxrs5cxhtHYr3PWD22uqDZdQ1t3PLDPfPVHO0a2gVcLv169uBDy9y7q106RbqTCJWNwCHHIxH80LfmTEcAd7cZWwT/UT1WdYfLefWGcP1lhI+In1oOJOHRfLajhOYDR40fmNnESOjQ5k12v1V8Bz9aV8BLBGRXGCJ9XtEJFFEzs0AEpFQ6+Pvdbn+SRE5KCIHgAXAgw7Go3mhpMgQ5qfH8ebuItoMHDR+ZVshJhG+N2uEYTFo7veDOSMpqDzLxmPGjVPlVdSzs/A0t8wYbshMNYcSgVKqWim1SCmVZv182nq8VCm1zOa8RqVUtFKqtsv131NKTVJKZSilru0ceNZ8z/+bMZzK+hY+P2xM0ZD65jbe3l3M1RkJxA8ONiQGzRjLJiWQEBHMi5uPGxbDS1sKCfT349vTjRmb0u1fzSMsGBvHiOhQnv8yH6Xc30R/a3cxDS3t/CBrlNvvrRkrwOTH7bNHsi2/muzS2t4vcLKK+mbe/bqYb09PNmymmk4Emkcw+Qn/Oi+F/cW1bM2rduu9O8yKV7YdJ3PEEDKSI916b80z3HrJcEIDTby8pdDt9/7r1kLaO8wsnzva7ffupBOB5jG+NT2JuPAgntmY59b7rjtSTtHpJt0a8GERoQHcnDmMVftLqKhrdtt965vb+MdXJ1g6MYGRMYPcdt+udCLQPEaQv4kfzR3Ntvxq9hXVuOWeSime3ZhPUmQIl4+Pd8s9Nc9055yRtJsVr24vdNs9/7njJPXN7dx1WYrb7tkdnQg0j3LrpcOJCAngmQ3uaRWsPVzOvqIa7luY6radHjXPNCJ6EEsnDuWVrYVuqZPR0t7BS1uOMyc1mknJES6/38Xon3zNo4QF+XP77JGsPVzOsfJ6l96rw6z4w5ocRscMMmy2huZZfnp5Os3tZv78hevfiLy1u5iK+hbDWwOgE4Hmge6cPZJBgSZ+/+lRl97ng70l5FY08NPL03VrQAMgJTaM71wyjNd2nOBEtetqFdQ2tfH058eYMSrKIyrg6Z9+zeMMGRTI/YvSWH+0gg0u2oyutd3M0+uOMTFpMEsnDnXJPTTv9JNFafj7+fGHtcdcdo//W5/LmcZWfnX1eI/Y6lwnAs0j3TlnFKNjBvHrjw/T2u781cav7zxJ8ZkmHrpiLH5+xv8iap4jbnAw/5I1io/2l3Kw2PnrCgoqG3hlWyHfyRzGxCRjxwY66USgeaRAfz9+dc14jled5a9bnbvis7SmiT+szWF2SjTz0oxvlmueZ/lloxkSGsCvP852euGa335yhOAAEz+9PN2pz+sInQg0jzU/PY7F4+L40/pcyp00t1spxSPvHqDDrFhxY4ZHNMs1zzM4OICfLxvHrsIzvLi5wGnPu+FoBeuPVnDvwlRiwz2n3oVOBJpH+/erx9NmVvzs7f1OeWf22o6TbM6t4ufLxjE8OtQJEWoD1benJ3PlhKH8YW0Oh0vrHH6+U7XN/Ozt/YyJD+POOSMdD9CJdCLQPNqI6EE8fs0ENudW8fTnjg3enag+yxOrjzA3LYbvXjrcSRFqA5WI8MSNk4gMDeQnb+6lua2j38/V1mHmvte/pqmtg2e+O40gf5MTI3WcTgSax7t1xjC+kzmMP2/IY232qX49R11zG/f+cy8mEX7/Ld0lpNknalAgT307g2PlDfz2kyP93hDxD2ty2FV4ht/dOInUuHAnR+k4nQg0jyci/Od1E8hIjuCnb+0nr6KhT9c3tLRz5193caSsjv+5ZQqJkSEuilQbiOanx/GjuaP4+1cnWPHp0T4ngw/2lvD8pgJumzmc66YkuShKx+hEoHmF4AATz9423bJn+3Pb2JZfZdd1Ta0d/Msru9hXVMP/3TqVReP0fkJa3/182Ti+P2sEz28q4Dd2tgw697H6yZv7mDEqil9eNd4NkfaPQ4lARG4SkWwRMYtI5kXOu1JEckQkT0QetTkeJSKfi0iu9fMQR+LRBrakyBDeu3s2sWFBfO+lnfx9e+FFfyEPldRy6wtfsbPwNP9982SWTkro8VxNuxgR4T+vncCdc0by0pbjPPzOAaovsh9Re4eZn79/iN9/dpRrJifytx/MIDjAs8YFbIkjRUBEZBxgBp4HfqaU2t3NOSbgGJZSlcXALuBWpdRhEXkSOK2UWmFNEEOUUo/0dt/MzEy1e/cFt9J8RH1zGw++uY91RyqYOTqKb01L5sqJQwkPDqC13UzxmUae3ZjPO18XExUayK+vm8hVGToJaI5TSvGHtTk8uzGfkAATP5w7mjtmjyQyNAARoaK+mbd3F/PPHScpqWningUp/HRJuscsWhSRPUqpC960O5QIbJ58Iz0nglnA40qpK6zfPwaglPqdiOQA85VSZdZC9huVUr2ustCJQOswK17aUsBrO05yorqRIH8/woP9qWpoBSDAJNw5ZxT3LkxlcHCAwdFqA01eRT1/XHuMTw9ZJi+Y/ITBwf7UN7fTblbMSY3mztmjWOxhW5v3lAj83XDvJKDI5vti4FLr1/GddYqtySCupycRkeXAcoDhw/XUP19n8hOWz0vhR3NHs7eoho/2l9Lc1kH84GCGDg5mdkqMXieguUxqXDjP3jadg8W1bM2vor65jbqmdsKC/fn29GRSYsOMDrFPek0EIrIO6G5Xrl8opT604x7dtYn63AxRSq0EVoKlRdDX67WBSUSYNnwI04br4SXN/SYlRxheS8AZek0ESqnFDt6jGBhm830yUGr9ulxEEmy6hlyz1aSmaZrWI3dMH90FpInIKBEJBG4BVlkfWwXcbv36dsCeFoamaZrmRI5OH71BRIqBWcAnIrLGejxRRFYDKKXagXuBNcAR4C2lVLb1KVYAS0QkF8usohWOxKNpmqb1nVNmDbmbnjWkaZrWdz3NGtIrizVN03ycTgSapmk+TicCTdM0H6cTgaZpmo/zysFiEakETvTz8hjAvq0rPZ9+LZ5noLwO0K/FUznyWkYopWK7HvTKROAIEdnd3ai5N9KvxfMMlNcB+rV4Kle8Ft01pGma5uN0ItA0TfNxvpgIVhodgBPp1+J5BsrrAP1aPJXTX4vPjRFomqZp5/PFFoGmaZpmQycCTdM0H+dTiUBErhSRHBHJs9ZI9joiMkxENojIERHJFpEHjI7JUSJiEpG9IvKx0bE4QkQiReQdETlq/f+ZZXRM/SUiD1p/vg6JyOsiEmx0TPYSkZdFpEJEDtkcixKRz0Uk1/rZ4ysZ9fA6nrL+fB0QkfdFJNIZ9/KZRCAiJuAvwFJgPHCriIw3Nqp+aQd+qpQaB8wE7vHS12HrASxblHu7/wU+U0qNBSbjpa9JRJKA+4FMpdREwISljoi3eAW4ssuxR4H1Sqk0YL31e0/3Che+js+BiUqpDOAY8JgzbuQziQCYAeQppQqUUq3AG8B1BsfUZ0qpMqXU19av67H8sUkyNqr+E5Fk4CrgRaNjcYSIDAbmAS8BKKValVI1hgblGH8gRET8gVC+qSro8ZRSm4DTXQ5fB7xq/fpV4Hp3xtQf3b0OpdRaa40XgK+wVHx0mC8lgiSgyOb7Yrz4DyiAiIwEpgI7DA7FEf8DPAyYDY7DUaOBSuCv1m6uF0VkkNFB9YdSqgT4A3ASKANqlVJrjY3KYfFKqTKwvJkC4gyOxxl+AHzqjCfypUQg3Rzz2rmzIhIGvAv8RClVZ3Q8/SEiVwMVSqk9RsfiBP7ANOBZpdRU4Cze0f1wAWv/+XXAKCARGCQitxkblWZLRH6BpZv4NWc8ny8lgmJgmM33yXhRc9eWiARgSQKvKaXeMzoeB8wBrhWRQixddQtF5B/GhtRvxUCxUqqzdfYOlsTgjRYDx5VSlUqpNuA9YLbBMTmqXEQSAKyfKwyOp99E5HbgauC7ykkLwXwpEewC0kRklIgEYhn8WmVwTH0mIoKlH/qIUuq/jY7HEUqpx5RSyUqpkVj+P75QSnnlO0+l1CmgSETSrYcWAYcNDMkRJ4GZIhJq/XlbhJcOfNtYBdxu/fp24EMDY+k3EbkSeAS4VinV6Kzn9ZlEYB1guRdYg+WH+i2lVLaxUfXLHOB7WN4977N+LDM6KA2A+4DXROQAMAV4wthw+sfaqnkH+Bo4iOXvhNds0SAirwPbgXQRKRaRfwFWAEtEJBdYYv3eo/XwOv4MhAOfW3/3n3PKvfQWE5qmab7NZ1oEmqZpWvd0ItA0TfNxOhFomqb5OJ0INE3TfJxOBJqmaT5OJwJN0zQfpxOBpmmaj/v/5mRYPf+svIEAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(X_train, model.predict(X_train), label = 'Train')\n",
"plt.scatter(X_test, model.predict(X_test), label = 'Test')\n",
"plt.plot(x,y, label = 'Original')\n",
"plt.title('Predicted')\n",
"plt.legend();"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Answer: Nope"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Let's add more neurons and more layers"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(tf.keras.layers.Dense(32, activation = 'linear'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'linear'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'linear'))\n",
"model.add(tf.keras.layers.Dense(1, activation = 'linear'))\n",
"model.compile(optimizer='adam',\n",
" loss='mse',\n",
" metrics=['mse'])\n",
"model.fit(X_train.reshape(-1,1), y_train, epochs = 1000, verbose = 0);"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(X_train, model.predict(X_train))\n",
"plt.scatter(X_test, model.predict(X_test))\n",
"plt.plot(x,y, label = 'Original')\n",
"plt.legend();\n",
"plt.title('Predicted');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Answer: Still Nope"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Let's try changing the activation function"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(tf.keras.layers.Dense(1, activation = 'relu'))\n",
"\n",
"model.compile(optimizer='adam',\n",
" loss='mse',\n",
" metrics=['mse'])\n",
"model.fit(X_train.reshape(-1,1), y_train, epochs = 1000, verbose = 0)\n",
"\n",
"plt.scatter(X_train, model.predict(X_train))\n",
"plt.scatter(X_test, model.predict(X_test))\n",
"plt.plot(x,y, label = 'Original')\n",
"plt.legend();\n",
"plt.title('Predicted');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Let's try changing the activation function and adding a layer"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(tf.keras.layers.Dense(32, activation = 'relu'))\n",
"model.add(tf.keras.layers.Dense(1, activation = 'linear'))\n",
"\n",
"model.compile(optimizer='adam',\n",
" loss='mse',\n",
" metrics=['mse'])\n",
"model.fit(X_train.reshape(-1,1), y_train, epochs = 1000, verbose = 0)\n",
"\n",
"plt.scatter(X_train, model.predict(X_train))\n",
"plt.scatter(X_test, model.predict(X_test))\n",
"plt.plot(x,y, label = 'Original')\n",
"plt.legend();\n",
"plt.title('Predicted');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Let's try adding some more layers"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(tf.keras.layers.Dense(32, activation = 'relu'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'relu'))\n",
"model.add(tf.keras.layers.Dense(1, activation = 'linear'))\n",
"\n",
"model.compile(optimizer='adam',\n",
" loss='mse',\n",
" metrics=['mse'])\n",
"model.fit(X_train.reshape(-1,1), y_train, epochs = 1000, verbose = 0)\n",
"\n",
"plt.scatter(X_train, model.predict(X_train))\n",
"plt.scatter(X_test, model.predict(X_test))\n",
"plt.plot(x,y, label = 'Original')\n",
"plt.legend();\n",
"plt.title('Predicted');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Let's try adding some more layers"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(tf.keras.layers.Dense(32, activation = 'relu'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'relu'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'relu'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'relu'))\n",
"model.add(tf.keras.layers.Dense(1, activation = 'linear'))\n",
"\n",
"model.compile(optimizer='adam',\n",
" loss='mse',\n",
" metrics=['mse'])\n",
"model.fit(X_train.reshape(-1,1), y_train, epochs = 1000, verbose = 0)\n",
"\n",
"plt.scatter(X_train, model.predict(X_train))\n",
"plt.scatter(X_test, model.predict(X_test))\n",
"plt.plot(x,y, label = 'Original')\n",
"plt.legend();\n",
"plt.title('Predicted');"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(tf.keras.layers.Dense(32, activation = 'sigmoid'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'sigmoid'))\n",
"\n",
"model.add(tf.keras.layers.Dense(1, activation = 'linear'))\n",
"\n",
"model.compile(optimizer='adam',\n",
" loss='mse',\n",
" metrics=['mse'])\n",
"model.fit(X_train.reshape(-1,1), y_train, epochs = 1000, verbose = 0)\n",
"\n",
"plt.scatter(X_train, model.predict(X_train))\n",
"plt.scatter(X_test, model.predict(X_test))\n",
"plt.plot(x,y, label = 'Original')\n",
"plt.legend();\n",
"plt.title('Predicted');"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"model = tf.keras.Sequential()\n",
"model.add(tf.keras.layers.Dense(32, activation = 'sigmoid'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'sigmoid'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'sigmoid'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'sigmoid'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'sigmoid'))\n",
"model.add(tf.keras.layers.Dense(32, activation = 'sigmoid'))\n",
"model.add(tf.keras.layers.Dense(1, activation = 'linear'))\n",
"\n",
"model.compile(optimizer='adam',\n",
" loss='mse',\n",
" metrics=['mse'])\n",
"model.fit(X_train.reshape(-1,1), y_train, epochs = 1000, verbose = 0)\n",
"\n",
"plt.scatter(X_train, model.predict(X_train))\n",
"plt.scatter(X_test, model.predict(X_test))\n",
"plt.plot(x,y, label = 'Original')\n",
"plt.legend();\n",
"plt.title('Predicted');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Conclusions:\n",
"\n",
"* Predicting sine waves is hard\n",
"* Using a linear function seems to always return a linear fit\n",
"* An activation layer like `relu` or `sigmoid` helps for a bit\n",
"* Still need a fairly large number of neurons and layers\n",
"\n",
"One problem is that there's only one feature, the $x$-value of each point. Because these $x$-values don't repeat, there is limited information gained from each point that can be used for other points. Adding additonal features, such as ARIMA would be helpful\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.8.5"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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