PyCaret: Anatomy of Regression

提供方
Coursera Project Network
在此免费指导项目中,您将:

How to create a regression environment and compare model performance

Create best performing regression models

Using hyper parameter to tune models

在面试中展现此实践经验

Clock2 hours 15 mins
Intermediate中级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

In this 2 hour and 15 mins long project-based course, you will learn how to ow to set up PyCaret Environment and become familiar with the variety of data preparing tasks done during setup, be able to create, see and compare the performance of several models, learn how to tune your model without doing an exhaustive search, create impressive visuals of models, interpret models with the wrapper around SHAP Library and much more & all this with just a few lines of code. Note: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

必备条件

Familiar with regression models, Sklearn and Python

您要培养的技能

  • PyCaret
  • Machine Learning
  • Python Programming
  • regression
  • Auto ML

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. Task 1: Import Data, Initial dataset check and setup Pycaret environment

  2. Task 2: Create regression environment and compare model performance

  3. Task 3: Create best performing regression models

  4. Task 4: Hyper Parameter tuning the models

  5. Task 5: Stacking & Ensemble

  6. Task 6: Visualize and interpret the machine learning model

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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常见问题

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