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  1. Learn how to use machine learning to predict survival on the Titanic and explore the data and models. This web page may have a syntax error and crash on some browsers.

    • Titanic Tutorial

      Explore and run machine learning code with Kaggle Notebooks...

  2. Learn how to use DataLab and Pandas to prepare and analyze the Titanic dataset for a Kaggle competition. Follow the steps to import, preprocess, and visualize the data, and submit your results to the competition.

  3. Learn how to use data from the Titanic disaster to build a machine learning model that predicts survival outcomes. This tutorial covers data exploration, feature engineering, model training, evaluation, and optimization with Kaggle Notebooks.

  4. Learn how to use Python and PyData tools to analyze the Titanic disaster data and predict survival outcomes. This notebook provides examples of data handling, visualization, and machine learning techniques for the Kaggle Titanic: Machine Learning from Disaster competition.

  5. Sep 30, 2019 · In this video, Kaggle data scientist Dr. Rachael Tatman walks you through the Titanic competition, explaining the details of the competition, where to get started and how to further improve...

  6. Jun 22, 2019 · Over the world, Kaggle is known for its problems being interesting, challenging and very, very addictive. 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.

  7. Oct 1, 2017 · How I got ~98% prediction accuracy with Kaggles Titanic Competition. First, I wanted to start eyeballing the data to see if the cities people joined the ship from had any statistical importance. Although travellers who started their journeys at Cherbourg had a slight statistical improvement on survival.