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This repository contains a data science project that focuses on predicting the survival of passengers aboard the Titanic during the tragic disaster. The goal is to build a machine learning model that can accurately predict whether a passenger survived or not based on various features such as socio-economic status, age, gender, and more.

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decsion-tree random random-forest titanic titanic-survival-prediction titanium

bhart_intern-task-2's Introduction

Bhart_Intern-Task-2

Titanic Classification : Make a system which tells whether the person will be save from sinking. Key Features: Here,

Data Preprocessing is done i;e handle missing values, encode categorical features, and prepare the data for machine learning. Model Building: Utilize a Random Forest Classifier & decision tree classifier to train the prediction model on the labeled training dataset. Model Evaluation: Evaluate the model's performance using accuracy percent. Visualization: Explore survival trends based on different factors using interactive and informative plots. Predictions: Generate predictions for the test dataset Insights: Gain valuable insights into the factors that might have influenced survival during the Titanic disaster

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