Designed and implemented a recommendation system using Python that analyzes user interaction data to predict and recommend new software features, improving adoption rates.

Defined goals for content ranking, collaborated with cross-functional teams, able to learn and gather requirements to deliver a strategic roadmap for content ranking.

Developed a deep learning model using CNN (Convolutional Neural Networks) to classify kidney disease from medical images. The project includes data preprocessing, model design, and performance evaluation. It utilizes advanced tools such as TensorFlow, Keras, and DVC for managing the workflow. The model was trained and evaluated using metrics such as accuracy, precision, and AUC-ROC, providing insights into its classification performance.

Implemented this project to learn data cleaning techniques for large datasets and gain insights from the data using SQL queries.

Developed a Convolutional Neural Network (CNN) using Keras and TensorFlow to classify lung CT scans and predict malignancy, utilizing various data augmentation and preprocessing techniques.

Developed an advanced dashboard using Power BI to analyze and generate insights about revenue streams within the hospitality domain, helping stakeholders make data-driven decisions.

Performed comprehensive SQL-based analysis on COVID-19 data, including infection and death rates, population impact, and vaccination trends across countries and continents.

Applied fundamental machine learning algorithms to predict outcomes using different datasets, including the UCI Adult dataset. The project involves data preprocessing, model tuning, and evaluation with cross-validation and ROC curves.