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This Kaggle competition, "Titanic - Machine Learning from Disaster," challenges participants to predict whether passengers on the Titanic survived or not based on various passenger attributes such as age, gender, and ticket class. It's a great introduction to machine learning and data analysis.

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titanic---machine-learning-from-disaster---kaggle's Introduction

Titanic - Machine Learning from Disaster

Introduction

This Kaggle competition, "Titanic - Machine Learning from Disaster," challenges participants to predict whether passengers on the Titanic survived or not based on various passenger attributes such as age, gender, and ticket class. It's a great introduction to machine learning and data analysis.

Data

The dataset for this competition contains information about passengers, including whether they survived or not. The dataset is split into a training set and a test set for model evaluation.

Goal

The primary objective is to build a machine learning model that accurately predicts the survival outcome for passengers in the test set.

File Descriptions

  • train.csv: The training dataset with labeled survival outcomes.
  • test.csv: The test dataset where you need to make predictions.
  • gender_submission.csv: A sample submission file with the correct format.

Evaluation

Model performance is evaluated based on accuracy, i.e., the percentage of correctly predicted outcomes.

Instructions

  1. Download the dataset from the Kaggle competition page.
  2. Use a Jupyter Notebook or any preferred data analysis tool to build and train your machine learning model.
  3. Make predictions on the test set and format the results according to the guidelines provided.
  4. Submit your predictions to Kaggle and see how well your model performs.

Helpful Resources

  • Kaggle Competition Page: For the competition details, data, and leaderboards.
  • Kaggle Kernels: Check out and learn from other Kaggle users' notebooks related to this competition for inspiration and guidance.

Best of luck with your machine learning journey and enjoy the Titanic competition!

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