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prediting risk according to givn details
Inspiration
DataGuard AI is a machine-learning project designed to analyze datasets, identify unusual patterns, and predict potential risks. The idea was inspired by the need to turn raw data into useful insights that can support faster decision-making.
I built the project using Python and common Data Science libraries. The workflow includes data preprocessing, exploratory data analysis, feature engineering, model training, and evaluation.
As this is my first hackathon project, I focused on learning how to take a real-world problem from raw data to a working machine-learning solution. The main challenges were understanding the dataset, handling missing or inconsistent values, selecting useful features, and choosing an appropriate model.
Through this project, I learned practical skills in data cleaning, visualization, machine learning, and presenting a Data Science solution.
Built With
- analysis
- data
- jupyter
- learning
- machine
- matplotlib
- numpy
- pandas
- python
- science
- scikit-learn
