{ "cells": [ { "cell_type": "markdown", "id": "9b2c0348", "metadata": {}, "source": [ "LabML02\n", "\n", "Consider the following data corresponding to \n", "\n", "url=\"https://github.com/masterfloss/data/raw/main/dataBitCoins1.xlsx\"\n", "\n", "It has the following data:\n", "* date - date\n", "* ElectPrice - price of electicity\n", "* BitcoinsPrice - bitcoins prince\n", "* TresBondsPrice - US tresury bonds price\n", "* BitcoinGoogleSerch - search index in Google (obtained from google trends)\n", "\n", "Create a model for price BitcoinsPrice prediction.\n", "\n", "1. Create a Regression model (OLS) using statsmodels library\n", "\n", "2. Create a Regression model (OLS) using sklearn library \n", "\n", "3. Create a Regression model using several comparing the accuracy of each model" ] }, { "cell_type": "code", "execution_count": null, "id": "a4c63a2d", "metadata": {}, "outputs": [], "source": [ "#" ] }, { "cell_type": "code", "execution_count": null, "id": "b1786e5e", "metadata": {}, "outputs": [], "source": [ "#" ] }, { "cell_type": "code", "execution_count": null, "id": "799f2a74", "metadata": {}, "outputs": [], "source": [ "#" ] }, { "cell_type": "code", "execution_count": null, "id": "5e729509", "metadata": {}, "outputs": [], "source": [ "#" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.8.12" } }, "nbformat": 4, "nbformat_minor": 5 }