Saddruddin Khan

I am a self-taught Machine Learning enthusiast with hands-on experience in Python, SQL, and key ML libraries such as Pandas, Matplotlib, and Scikit-learn. My journey in machine learning has been fueled by a passion for data and a desire to apply my skills in real-world projects. I am actively building a strong foundation using tools like Jupyter Notebook and Google Colab, which has allowed me to develop practical skills and a deeper understanding of machine learning concepts.

One of my notable projects includes the Pediatric Hemodynamic Shock Prediction, where I built a machine learning pipeline to predict the occurrence of hemodynamic shock within six hours in pediatric patients using clinical data. I executed data cleaning, missing value imputation, exploratory data analysis, feature scaling, and visualization techniques to enhance model accuracy. I trained and tuned an XGBoost classifier, achieving a macro F1-score of 0.94 on test data, and evaluated performance using confusion matrix and ROC-AUC analysis.

I am currently seeking a remote internship that will allow me to apply my skills in real-world machine learning projects and grow through collaboration. I am eager to contribute to a team and learn from experienced professionals in the field.