Dawood Khan

Created a classification model to predict heart disease, utilizing various evaluation metrics to assess model performance. Applied precision, recall, and F1-score to validate the model's accuracy.

Scraped real estate data from Zameen.com and developed a regression model to predict house prices. Focused on data cleaning, feature engineering, and enhancing model performance using Decision Trees.

Cleaned and preprocessed bulldozer auction data to build regression models for predicting sale prices. Improved model accuracy through extensive feature engineering and hyperparameter tuning.

Developed intelligent AI agents using CrewAI for brand compatibility scoring, designing collaborative roles such as researcher, scorer, and coach. Gained practical experience in prompt design, agent architecture, and justification logic through this project.

Participated in a competitive machine learning challenge involving a dataset with over 130,000 rows. Successfully implemented a full data pipeline for real-world prediction tasks.

Managed and processed a large dataset of 77 million rows, focusing on efficient data handling techniques. Developed scalable machine learning pipelines for large-scale prediction tasks.

Currently pursuing a Bachelor of Science in Data Science with an expected graduation in 2028. Focused on gaining expertise in machine learning, deep learning, LLMs, MLOps, and agentic workflows.