Titanic Survival Prediction Using Machine Learning

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

Understand the theory and intuition behind logistic regression classifier models

Build, train and test a logistic regression classifier model in Scikit-Learn

Perform data cleaning, feature engineering and visualization

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

In this 1-hour long project-based course, we will predict titanic survivors’ using logistic regression and naïve bayes classifiers. The sinking of the Titanic is one of the key sad tragedies in history and it took place on April 15th, 1912. The numbers of survivors were low due to lack of lifeboats for all passengers. This practical guided project, we will analyze what sorts of people were likely to survive this tragedy with the power of machine learning. Note: This course 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 Science
  • Python Programming
  • Machine Learning

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. Understand the Problem Statement and Business Case

  2. Import Libraries and Datasets

  3. Perform data visualization – Part 1

  4. Perform data visualization – Part 2

  5. Perform data cleaning and feature engineering

  6. Train a logistic Regression classifier model

  7. Evaluate a logistic regression classifier model

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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