PyCaret: Anatomy of Regression

提供方
Coursera Project Network
在此免費指導項目中,您將:

How to create a regression environment and compare model performance

Create best performing regression models

Using hyper parameter to tune models

在面試中展現此實踐經驗

Clock2 hours 15 mins
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

必備條件

Familiar with regression models, Sklearn and Python

您要培養的技能

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

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  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

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

常見問題

常見問題

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