https://github.com/harshil8705/titanic_survival_prediction

I have Created a Machine Learning Model based on the Logistic Regression algorithm. This Model is capable of predicting whether the person will survive or not survive based on the given data of that particular person.This Model is highly accurate in predicting the result.
https://github.com/harshil8705/titanic_survival_prediction

artificial-intelligence jupyter kaggle logistic-regression machine-learning matplotlib numpy pandas python seaborn titanic-kaggle titanic-survival-prediction

Last synced: 17 days ago
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I have Created a Machine Learning Model based on the Logistic Regression algorithm. This Model is capable of predicting whether the person will survive or not survive based on the given data of that particular person.This Model is highly accurate in predicting the result.

• Host: GitHub
• URL: https://github.com/harshil8705/titanic_survival_prediction
• Owner: harshil8705
• Created: 2024-10-28T05:12:43.000Z (21 days ago)
• Default Branch: main
• Last Pushed: 2024-10-28T05:29:09.000Z (21 days ago)
• Last Synced: 2024-10-28T08:49:56.924Z (20 days ago)
• Topics: artificial-intelligence, jupyter, kaggle, logistic-regression, machine-learning, matplotlib, numpy, pandas, python, seaborn, titanic-kaggle, titanic-survival-prediction
• Language: Jupyter Notebook
• Homepage: https://www.kaggle.com/competitions/titanic
• Size: 85 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Titanic_Survival_Prediction

I have Created a Machine Learning Model based on the Logistic Regression algorithm.

This Model is capable of predicting whether the person will survive or not survive based on the given data of that particular person.

This Model is highly accurate in predicting the result.

It has the Accuracy score of 0.800561797752809 i.e. approximately 80.05% on the Training data and the Accuracy score of 0.7932960893854749 i.e. approximately 79.33% on the Testing data.

Making this model Highly accurate in predicting the result of survived people in the titanic.