用scikit-learn预测销售收入

Predict Sales Revenue with scikit-learn

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Rhyme
Coursera
  • 完成时间大约为 2 个小时
  • 初级
  • 英语
注:本课程由Coursera和Linkshare共同提供,因开课平台的各种因素变化,以上开课日期仅供参考

你将学到什么

Build simple linear regression models in Python

Apply scikit-learn and statsmodels to regression problems

Employ explorartory data analysis (EDA) with seaborn and pandas

Explain linear regression to both technical and non-technical audiences

课程概况

In this 2-hour long project-based course, you will build and evaluate a simple linear regression model using Python. You will employ the scikit-learn module for calculating the linear regression, while using pandas for data management, and seaborn for plotting. You will be working with the very popular Advertising data set to predict sales revenue based on advertising spending through mediums such as TV, radio, and newspaper.

By the end of this course, you will be able to:
– Explain the core ideas of linear regression to technical and non-technical audiences
– Build a simple linear regression model in Python with scikit-learn
– Employ Exploratory Data Analysis (EDA) to small data sets with seaborn and pandas
– Evaluate a simple linear regression model using appropriate metrics

This course runs on Coursera’s hands-on project platform called Rhyme. On Rhyme, you will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Jupyter and Python 3.7 with all the necessary libraries pre-installed.

Notes:
– You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want.
– This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

课程大纲

Project: Predict Sales Revenue with Simple Linear Regression

In this project-based course, you will build and evaluate a simple linear regression model using Python. You will employ the scikit-learn module for calculating the linear regression, while using pandas for data management, and seaborn for plotting. You will be working with the very popular Advertising data set to predict sales revenue based on advertising spending through mediums such as TV, radio, and newspaper. By the end of this project, you will be able explain the core ideas of linear regression to technical and non-technical audiences, build a simple linear regression model in Python with scikit-learn, employ Exploratory Data Analysis (EDA) to small data sets with seaborn and pandas, and evaluate a simple linear regression model using appropriate metrics.

课程项目

Introduction and Overview

Loading the Data and Importing Libraries

Removing the Index Column

Exploratory Data Analysis (EDA)

Relationship between Predictors and Response

Creating the Simple Linear Regression Model

Evaluation and Model Parameters

Making Predictions with the Model

Model Evaluation Metrics

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