Logistic Regression for Classification using Julia

Offered By
Coursera Project Network
In this Guided Project, you will:

Balance data suing the SMOTE method.

Build a logistic regression model.

Clock1 hour 30 minutes
BeginnerBeginner
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

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.

Skills you will develop

Data ScienceMachine LearningLogistic Regressiondata preperationjulia

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  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

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.