Welcome to my ML-Engineering-Demo repository, where I showcase my machine learning engineering skills using the famous Titanic dataset from Kaggle. This project aims to build a comprehensive ML pipeline, demonstrating my expertise in data science and machine learning.
Current Status: Under Development 🚧
This project is a work in progress, and I am actively updating it with new features and improvements.
- Language: Python
- Key Libraries: Pandas, Scikit-Learn, MLflow, Ray
pip install -r requierements.txt
- Implement and evaluate different machine learning models.
- Develop a robust data processing pipeline.
- Optimize models for accuracy and efficiency.
- Data exploration and preprocessing implemented.
- Initial model training with basic algorithms.
- Integrate advanced ML/DL models.
- Improve model accuracy and performance.
Feel free to fork, contribute, or provide feedback to this project. Your input is highly appreciated!
For any inquiries or professional connections, fill free to reach out to me.
Background: Remote Sensing Data Scientist and Algorithm Developer with expertise in ML/DL models, data engineering, and satellite imaging.
Note: This project is part of my professional portfolio at TierraSpec and showcases skills relevant to space science and agri-tech applications.