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Titanic Survival Prediction Using Machine Learning

Offered By: Coursera Project Network via Coursera

Tags

Machine Learning Courses Data Analysis Courses Predictive Modeling Courses Logistic Regression Courses Naive Bayes Classifier Courses

Course Description

Overview

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.

Syllabus

  • Project Overview
    • In this project-based course, we will build, train and test a machine learning model to predict titanic survivors based on their features such as age, number of siblings, and ticket class. We will explore two machine learning algorithms, namely: (1) logistic regression classifier model and (2) Naive Bayes classifier model.

Taught by

Ryan Ahmed

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