Data Science Project -Predicting survival on the Titanic

Data Science Project -Predicting survival on the Titanic

In this data science project with Python, we will complete the analysis of what sorts of people were likely to survive.You will learn to use various machine learning tools to predict which passengers survived the tragedy.

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Nathan Elbert

Senior Data Scientist at Tiger Analytics

This was great. The use of Jupyter was great. Prior to learning Python I was a self taught SQL user with advanced skills. I hold a Bachelors in Finance and have 5 years of business experience.. I... Read More

Swati Patra

Systems Advisor , IBM

I have 11 years of experience and work with IBM. My domain is Travel, Hospitality and Banking - both sectors process lots of data. The way the projects were set up and the mentors' explanation was... Read More

What will you learn

Understanding the problem statement
Importing the dataset and importing libraries
Performing basic EDA and checking for null values
Imputing the null values filling them using appropriate method
Statistics summaries using describe function
Encoding categorical variables
Using graphs to visualize data visually
Using groupby() function method to visualize the relationship between different data
How to use pivot tables
Understanding Overfitting and Cross Validation
Applying Logistic Regression for modeling
Using Cross Folds Validation to prevent overfitting
Making predictions for the test dataset

Project Description

The sinking of the RMS Titanic is one of the most infamous shipwrecks in history.  On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships.This data science project will give you introdcution on how to use Python to apply various machine learning techniques  to the RMS Titanic dataset and predict which passenger would have survived the tragedy.

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Curriculum For This Mini Project

21-Nov-2015
04h 12m