<strike id="jrjdx"><ins id="jrjdx"></ins></strike>

<address id="jrjdx"></address>

    <listing id="jrjdx"><listing id="jrjdx"><meter id="jrjdx"></meter></listing></listing>
    <address id="jrjdx"></address><form id="jrjdx"><th id="jrjdx"><th id="jrjdx"></th></th></form>
    <address id="jrjdx"><address id="jrjdx"><listing id="jrjdx"></listing></address></address>
    <noframes id="jrjdx">

    <noframes id="jrjdx">
    <form id="jrjdx"></form><form id="jrjdx"></form>

      <noframes id="jrjdx"><address id="jrjdx"><listing id="jrjdx"></listing></address>
      <noframes id="jrjdx">

      課程目錄:用scikit-learn預測銷售收入培訓
      4401 人關注
      (78637/99817)
      課程大綱:

                用scikit-learn預測銷售收入培訓

       

       

       

      Project: Predict Sales Revenue

      with Simple Linear RegressionIn 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.

      日韩不卡高清