Logistic Regression&application as Classification Algorithm

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

C​reate a Linear Regression model

C​reate a Logistic Regression model and compare with Linear model

P​erform a classifcation task with Logit model

Clock2 hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this project, you will learn about Logistic Regression and its application as Classification Algorithm. The project demonstrates the theoretical background of Logistic Regression using the Sigmoidal function. It also explains the suitability of linear vs logistic regression to answer the specific types of research questions. Finally, it covers an implementation of classification algorithm using logit model. The project utilizes the 'Candy' dataset for illustrative purpose.

Skills you will develop

Logistic RegressionData AnalysisLinear RegressionClassification Algorithm

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. Introduction to Logistic Regression

  2. Dataset and Linear Regression

  3. Logistic Regression and comparison with Linear Regression

  4. Classification Algorithm - Logit Model

  5. Model Evaluation

  6. Model Training

  7. Model Testing

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

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