Projects
Transformer Based Sentiment Analysis For E-Commerce Insight
Developed an AI-driven sentiment analysis tool to efficiently process over 500,000 Amazon reviews, providing businesses with real-time, actionable insights into customer feedback. By improving classification accuracy by 20% using RoBERTa and reducing manual review time by 50%, this tool enables companies to quickly identify customer sentiments, trends, and pain points. The scalable platform, combined with a user-friendly GUI, makes it accessible to non-technical teams, empowering marketing, customer service, and product development departments to make data-driven decisions that enhance customer satisfaction and drive business growth.
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AI Sales Predictor
Developed a machine learning-based sales forecasting model to help businesses accurately predict future sales and optimize resource allocation. By leveraging Python for extensive data preprocessing with Pandas and NumPy, data quality was improved, resulting in a 35% increase in forecasting accuracy. Advanced machine learning techniques were applied using Scikit-learn, and the model’s reliability was validated through RMSE and R² metrics. This forecasting tool enables businesses to make informed decisions on inventory management, budgeting, and marketing strategies, ultimately enhancing operational efficiency and driving revenue growth.
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Ultimate Tic-Tac-Toe
Developed an advanced Ultimate Tic-Tac-Toe application designed to enhance user engagement and deliver a challenging gaming experience. Leveraged GitHub for version control in a multi-developer environment and conducted scrum meetings, fostering collaboration and efficient workflow management. The front-end was built using sophisticated HTML and CSS techniques, while Python, Flask, and SQL were utilized for robust back-end functionality and effective session management. Integrated AI-driven computer strategies, resulting in a 75% increase in game difficulty, offering users a more dynamic and engaging experience. This project showcases the seamless integration of AI with interactive web applications, highlighting practical applications in both software development and game design.
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TalkWave
Developed a Python-based automation tool, TalkWave, designed to convert PDF documents into clear, natural-sounding speech. Utilizing pyPDF2 for text extraction and Google Text-to-Speech (gTTS) for audio generation, the software delivers accurate speech output with a natural voice tone, making it a valuable resource for individuals with visual impairments, busy professionals, and those seeking hands-free document review. Implemented a user-friendly GUI using Tkinter, ensuring an intuitive and visually appealing interface that enhances accessibility for non-technical users. This project highlights the practical application of Python in creating assistive technologies and improving user experience through automation.
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