View Notebook: Steel Plate Defect Prediction

View Notebook: Prediction of Obesity Risk

Demonstrated proficiency in applying machine learning techniques to solve real-world problems through Kaggle competitions.

Key Achievements:

• Classification Challenges: Successfully tackled multi-label classification tasks, such as identifying defects in steel plates and predicting health outcomes based on lifestyle factors.

• Algorithm Selection and Implementation: Effectively leveraged algorithms like XGBoost and logistic regression, demonstrating an understanding of their strengths and trade-offs.

• Data Preprocessing and Feature Engineering: Proactively addressed challenges like multi-label classification and categorical variables through techniques like one-hot encoding and strategic label handling.