A collection of projects showcasing my expertise in data science, software development, and machine learning, demonstrating innovative solutions to real-world problems.
In this project, three different classifiers, including Random Forest, Decision Tree,and Multinomial logistic regression was applied in a distributed fashion to predict the genre of music based on various features. The models accuracy and F1 score are calculated and compared their effectiveness, alongside data processing techniques, to identify the effectiveness of these techniques for music genre classification.
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The Auto-ML project automates machine learning tasks for regression and classification using Python, Pandas, pyCaret, and Streamlit. It provides functionalities for data uploading, profiling, model training, and prediction, making it easy for users to analyze and make predictions on their datasets without extensive manual intervention.
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A book recommendation matrix file (CSV), generated using MapReduce HPCI and employing user-based collaborative filtering technique, containing the likeability scores of the top 10 books for over 9000 books. Streamlit was utilized to develop a user interface (UI) for the recommendation system.
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The project aims to provide the construction team with data-driven insights using Tableau data visualization to optimize room renovation and construction decisions for a Hotel. The project tend to identify rooms needing renovation, suggested high-demand room types with optimal rates, and determined parking slot requirements.
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It utilizes machine learning and an improvised Big Five personality method to sort users into Hogwarts houses based on their personality traits, creating an engaging and interactive experience reminiscent of the Harry Potter series.
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The project involves developing and migrating Verizon legacy applications to AWS, It focus on REST microservices, particularly enhancing the payment and billing conversational layer. I actively contributed across vital development stages, including requirement analysis, development, testing, and bug resolution. Operating within Agile-Scrum frameworks, I collaborated seamlessly with architects and technical managers to create well-designed, resilient software components.
This project focused on healthcare software, I spearheaded comprehensive security tests, conducted meticulous risk assessments, and conducted in-depth data analysis. My collaborative endeavours with cross-functional teams played a pivotal role in identifying vulnerabilities and implementing robust solutions, resulting in the revelation of actionable insights. The primary project objective was to elevate data security measures for healthcare applications and datasets. I applied rigorous protocols to strengthen protection against potential vulnerabilities, thereby ensuring the utmost integrity and reliability of healthcare data.