Master in Computer Application
Kalinga Institute of Industrial Technology
2024 - 2026 CGPA: 8.0
Hello! I am currently pursuing a Master's in Computer Application with a strong background in data analysis, machine learning, and data visualization. I am passionate about solving real-world problems using data and automation tools.
My technical toolkit includes Python, Scikit-learn, TensorFlow, Power BI, SQL, and Excel. I have completed several hands-on projects including Fake News Detection, Play Store Sentiment Analysis, and Brain Tumor Detection.
View My ProjectsA quick look at my academic foundation and practical industry experience.
Kalinga Institute of Industrial Technology
2024 - 2026 CGPA: 8.0
Gopabandhu Science College
2020 - 2023 CGPA: 6.70
LabMentixx Sep 2025 - Present
Built and improved machine learning pipelines for real-world datasets, including data preprocessing, model training, and performance evaluation. Also supported experimentation in NLP and model tuning to improve prediction quality.
Google Aug 2025 - Sep 2025
Worked on applied AI tasks focused on model prototyping and analysis workflows, with emphasis on clean data handling, experiment tracking, and communicating insights through clear visual and technical reports.
Oasis Infobyte Jul 2025 - Aug 2025
Solved real-world data science problems by building machine learning models for classification and prediction tasks, enhancing model accuracy and performance.
Evoastra Ventures Jul 2025 - Sep 2025
Contributed to AI-powered solutions by developing intelligent systems that automated processes and improved user interaction using deep learning and NLP techniques.
Conducted data visualization and nutritional analysis of McDonald's menu items to uncover insights on calories, protein, and fat distribution across categories using Python and Matplotlib.
This project analyzes Google Play Store app reviews and metadata using Python. It leverages Pandas, NumPy, and Matplotlib to perform Exploratory Data Analysis (EDA) and sentiment analysis. The goal is to uncover correlations between app features such as installs, ratings, and review sentiment to support better product decisions.
A Machine Learning based project that predicts house prices by analyzing key features like area, location, number of rooms, and more. The model helps in estimating accurate property values using regression techniques.
An Exploratory Data Analysis project focused on uncovering insights from retail sales data. It identifies sales trends, analyzes store performance, and detects seasonal patterns to support better business decisions.