Decision Tree and Random Forest Classification using Julia

4.6
12 個評分
提供方
Coursera Project Network
在此指導項目中,您將:

Learn about stumps, decision trees and random forests.

Learn how to check the performance of a decision tree and random forest.

Work with a real world dataset.

Clock1 hour 30 minutes
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

This guided project is about glass classification using decision tree classification and random forest classification in Julia. It is ideal for beginners who do not know what decision trees or random forests are because this project explains these concepts in simple terms. While you are watching me code, you will get a cloud desktop with all the required software pre-installed. This will allow you to code along with me. After all, we learn best with active, hands-on learning. Special features: 1) Simple explanations of important concepts. 2) Use of images to aid in explanation. 3) Challenges to ensure that the learner gets practice. 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.

您要培養的技能

  • Decision Tree
  • Data Analysis
  • Random Forest
  • Classification Algorithms
  • julia

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. Learn about stumps and their importance.

  2. Learn how to build a decision tree.

  3. Learn how to prune a decision tree.

  4. Learn how to build a random forest.

  5. Learn how to do hyper parameter tuning

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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