Logistic Regression for Classification using Julia

提供方
Coursera Project Network
在此免費的指導 項目中,您將:

Balance data suing the SMOTE method.

Build a logistic regression model.

在面試中展現此實踐經驗

Clock1 hour 30 minutes
Beginner面向初學者
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 book genre classification using logistic regression in Julia. It is ideal for beginners who do not know what logistic regression is 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) Use a real world dataset. 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

Learners who do not know about logistic regression or Julia programming.

您要培養的技能

Data ScienceMachine LearningLogistic Regressiondata preperationjulia

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. Exploratory data analysis

  2. One-hot encoding

  3. Check if data is balanced

  4. Build a logistic regression model

  5. Check model accuracy

  6. Check ROC numbers to determine number of false positives and false negatives.

  7. Using SMOTE to correct the imbalanced data

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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