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.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
د.جوب منطقة حرة ذ.م.م. 2026 © جميع الحقوق محفوظة
