Zayed Ansari

Results-driven Machine Learning Engineer with practical experience in data preprocessing, model building, and deployment. Demonstrated ability to develop innovative AI solutions that enhance operational efficiency and drive business outcomes. Strong analytical skills complemented by a commitment to continuous learning and professional growth.

Machine Learning Heart Disease Predictor

• Developed a predictive model using UCI Heart Disease dataset to classify heart disease risk with high accuracy
• Implemented and compared multiple machine learning algorithms, including Random Forest and Logistic Regression
• Conducted comprehensive feature importance analysis to identify key predictive factors
• Achieved reliable performance through rigorous model evaluation techniques

Student Performance Prediction Model

• Created a predictive machine learning model forecasting student academic performance
• Applied advanced data preprocessing and feature scaling techniques
• Utilized Random Forest and Linear Regression algorithms for robust prediction
• Validated model reliability through cross-validation and RMSE metrics

Open Source Contribution to Scikit-Learn

• Identified and successfully resolved a critical bug in scikit-learn's model evaluation functionality
• Contributed to improving the reliability of a widely-used machine learning library
• Demonstrated problem-solving skills and commitment to open-source software development