AI & Machine Learning enthusiast focused on building intelligent, data-driven systems.
I am a data science enthusiast with a growing interest in data analysis, machine learning, and algorithms. I enjoy working with real-world datasets to uncover patterns, extract insights, and build predictive models with proper evaluation. I have hands-on experience with Python, SQL, and core data science libraries including Pandas, NumPy, Scikit-learn, and Matplotlib. Through academic coursework and practical projects, I have worked on data preprocessing, exploratory data analysis, model training, and performance evaluation.
Alongside data science, I have a strong background in data structures and algorithms and experience developing applications in C, C++, and Java. These experiences have strengthened my problem-solving and analytical skills, and I am continuously learning to apply data science and machine learning techniques to real-world problems.
Developed a CNN-based deep learning system to classify kidney conditions Normal, Cyst, Stone, and Tumor from CT scan images with preprocessing, resizing and exploratory analysis. The custom model was evaluated using accuracy, precision, recall, and confusion matrix, demonstrating AI’s potential to support early and reliable medical diagnosis.
View Project ↗This project applies data science and machine learning to predict diabetes using medical and lifestyle data, incorporating exploratory analysis, and supervised classification models to identify key indicators such as BMI, HbA1c, and blood glucose levels.
View Project ↗This project focuses on applying Data Science and Machine Learning techniques to analyze AI, ML, and Data Science job information. Through exploratory data analysis and predictive modeling, the goal is to identify key factors influencing salaries and to strengthen practical skills in data preprocessing, feature analysis, and salary prediction.
View Project ↗