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Jun 22, 2019 · One of these problems is the Titanic Dataset. So summing it up, the Titanic Problem is based on the sinking of the ‘Unsinkable’ ship Titanic in the early 1912. It gives you information about multiple people like their ages, sexes, sibling counts, embarkment points and whether or not they survived the disaster.
Predict survival on the Titanic and get familiar with ML basics. ... New Notebook. table_chart. New Dataset. tenancy. New Model. emoji_events. New Competition ...
The Titanic Data Science Project seeks to predict passenger survival outcomes from the infamous 1912 disaster using machine learning. Our goal is to identify key survival determinants by analyzing a dataset that includes age, gender, class, and fare, among other variables.
Introduction¶. The Titanic sank on April 15, 1912 during her maiden voyage. After colliding with an iceberg, 1502 of its 2224 passengers died. The data set investigated in the following sections contains detailed information about 891 passengers.
Titanic Dataset - Train.csv will contain the details of a subset of the passengers on board (891 to be exact) and importantly, will reveal whether they survived or not, also known as the “ground truth”. The `test.csv` dataset contains similar information but does not disclose the “ground truth” for each passenger.
Nov 24, 2021 · Note: This notebook is my analysis of the titanic dataset to obtain any meaningful insights from the data and scores an accuracy of ~80 percent (top 5 percent of 14k entries on Kaggle) . Let’s ...
