mirror of https://github.com/kubeflow/examples.git
113 lines
2.3 KiB
Plaintext
113 lines
2.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Simple Machine Learning Model\n",
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"\n",
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"Credit: [Raman Sah](https://towardsdatascience.com/simple-machine-learning-model-in-python-in-5-lines-of-code-fe03d72e78c6)\n",
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"\n",
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"1. Generate data\n",
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"1. Train a model\n",
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"1. Make a prediction"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from random import randint\n",
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"from sklearn.linear_model import LinearRegression"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Generate data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"TRAIN_SET_LIMIT = 1000\n",
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"TRAIN_SET_COUNT = 100\n",
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"\n",
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"TRAIN_INPUT = list()\n",
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"TRAIN_OUTPUT = list()\n",
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"for i in range(TRAIN_SET_COUNT):\n",
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" a = randint(0, TRAIN_SET_LIMIT)\n",
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" b = randint(0, TRAIN_SET_LIMIT)\n",
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" c = randint(0, TRAIN_SET_LIMIT)\n",
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" op = a + (2*b) + (3*c)\n",
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" TRAIN_INPUT.append([a, b, c])\n",
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" TRAIN_OUTPUT.append(op)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Train a model"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"predictor = LinearRegression(n_jobs=-1)\n",
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"predictor.fit(X=TRAIN_INPUT, y=TRAIN_OUTPUT)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Make a prediction"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"X_TEST = [[10, 20, 30]]\n",
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"outcome = predictor.predict(X=X_TEST)\n",
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"coefficients = predictor.coef_\n",
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"\n",
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"print('Outcome : {}\\nCoefficients : {}'.format(outcome, coefficients))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.15"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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