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.
- Competition Link: Titanic: Machine Learning from Disaster
- Objective: Predict the survival of passengers on the Titanic based on provided data.
- notebooks/: Jupyter notebooks with step-by-step analysis, feature engineering, and model training.
- data/: Dataset files.
- images/: Visualizations and images used in the notebooks.
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Clone the repository:
git clone https://github.com/Farhakousar1601/titanic_ml_my_first_competition_kaggle.git
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Navigate to the project directory:
cd titanic_ml_my_first_competition_kaggle -
Follow the Kaggle Competition Link: Titanic: Machine Learning from Disaster
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Join the Competition:
- Click on "Join Competition" to participate.
- Download the dataset from the "Data" tab on the competition page.
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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.
- Open the Jupyter notebooks in the
- Utilized advanced machine learning algorithms for accurate predictions.
- Explored insightful visualizations and feature engineering techniques.
- Python
- Jupyter Notebooks
- Scikit-learn
- Pandas
- Matplotlib
- Seaborn
- Top 10% in Kaggle competition.
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!