Entry-level Computer Science graduate with skills in Python, Machine Learning, C++, and SQL. Experienced in building ML projects such as Churn Prediction and Autocorrect Systems with strong data analysis and problem-solv…
Entry-level Computer Science graduate with skills in Python, Machine Learning, C++, and SQL. Experienced in building ML projects such as Churn Prediction and Autocorrect Systems with strong data analysis and problem-solving abilities. Currently learning Generative AI and seeking an opportunity to apply technical skills and grow in a professional environment.
Cleaned and preprocessed customer data using Pandas and NumPy; performed feature selection and exploratory analysis., Trained Logistic Regression model using 75/25 train-test split and K-Fold Cross Validation., Designed and executed complex SQL queries using JOINs, nested subqueries, and aggregations to analyze multi-table business data., Built a CEO-level Power BI dashboard presenting KPIs such as revenue trends, growth rates, and operational performance.
Developed an ML-based autocorrect system using large text datasets and text preprocessing techniques., Applied encoding methods and trained multiple models to improve prediction accuracy., Evaluated and optimized model performance, achieving ~85.67% accuracy., Optimized SQL queries, improving execution performance by ~30%, reducing dashboard refresh time., Performed data validation and cleaning to ensure accuracy and consistency before visualization., Translated analytical results into clear business insights to support executive decision-making.
Developed multiple academic and technical projects with a strong focus on Machine Learning and software development. Built a Churn Prediction System using Python, where customer data was cleaned, preprocessed, and trained using Logistic Regression with K-Fold Cross Validation, achieving approximately 86% accuracy. Also designed an Autocorrect System using Machine Learning, trained on large text datasets with encoding and optimization techniques, achieving 85.67% accuracy. In addition, implemented a Home Automation System using C++ to strengthen system-level programming skills and created a web-based Garbage Collection System using HTML and CSS to improve user interaction and information management.
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