{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Lab08 ##\n", "\n", "\n", "\n", "#### The purpose ####\n", "\n", "explain the real estate market value\n", "\n", "\n", "Create a regression model explaining real estate prices. Use the following dataset: https://github.com/masterfloss/data/blob/main/realEstate.xlsx?raw=true.\n", "\n", "from sklearn.XXXX import XXXXX\n", "\n", "model = XXXXX()\n", "\n", "result = model.fit(features,target)\n", "\n", "y_pred = result.predict(X_test)\n", "\n", "1. Use the \"traditional approaches to solve the problem (OLS,RIDGE,LASSO,polinomial)\n", "\n", "See: https://scikit-learn.org/stable/supervised_learning.html#supervised-learning\n", "\n", "2. Use neural networks \n", "\n", "see: https://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPRegressor.html\n", "\n", "3. Use Keras\n", "\n", "see: https://keras.io/\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 }