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This repository contains my solution for the Titanic Machine Learning competition on Kaggle. It's my first competition, and I explore various machine learning techniques to predict passenger survival. The Jupyter notebook includes data analysis, feature engineering, and model training. Feel free to explore, learn, and contribute!

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FarhaKousar1601/titanic_ml_my_first_competition_kaggle

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🚢 Titanic Machine Learning Competition

Titanic Kaggle LinkedIn GitHub

🚀 Overview

Welcome to my Titanic Machine Learning competition project! This repository contains my solution for the Titanic Kaggle competition. Whether you're a beginner or experienced, this project is designed to help you understand machine learning and data science techniques.

ℹ️ Kaggle Competition Details

📁 Repository Contents

  • notebooks/: Jupyter notebooks with step-by-step analysis, feature engineering, and model training.
  • data/: Dataset files.
  • images/: Visualizations and images used in the notebooks.

💻 Getting Started for Beginners

  1. Clone the repository:

    git clone https://github.com/Farhakousar1601/titanic_ml_my_first_competition_kaggle.git
  2. Navigate to the project directory:

    cd titanic_ml_my_first_competition_kaggle
  3. Follow the Kaggle Competition Link: Titanic: Machine Learning from Disaster

  4. Join the Competition:

    • Click on "Join Competition" to participate.
    • Download the dataset from the "Data" tab on the competition page.
  5. Start the Jupyter Notebooks:

    • Open the Jupyter notebooks in the notebooks/ directory.
    • Follow the instructions and code provided in the notebooks to analyze the Titanic dataset and develop machine learning models.

✨ Project Highlights

  • Utilized advanced machine learning algorithms for accurate predictions.
  • Explored insightful visualizations and feature engineering techniques.

👀 Preview

Titanic Analysis

🛠️ Technologies Used

  • Python
  • Jupyter Notebooks
  • Scikit-learn
  • Pandas
  • Matplotlib
  • Seaborn

🏆 Achievements

  • Top 10% in Kaggle competition.

📜 License

This project is licensed under the MIT License - see the LICENSE.md file for details.


👉 Access the Kaggle Kernel here.

Feel free to connect with me on Kaggle, LinkedIn, and GitHub for more updates!

About

This repository contains my solution for the Titanic Machine Learning competition on Kaggle. It's my first competition, and I explore various machine learning techniques to predict passenger survival. The Jupyter notebook includes data analysis, feature engineering, and model training. Feel free to explore, learn, and contribute!

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