Anuranj V.V. is a dedicated Data Science student at Amity University with a strong foundation in data analysis, visualization, and programming. Having completed a Data Analysis Masterclass and a Tableau workshop, Anuranj…
Anuranj V.V. is a dedicated Data Science student at Amity University with a strong foundation in data analysis, visualization, and programming. Having completed a Data Analysis Masterclass and a Tableau workshop, Anuranj possesses practical expertise in Python, SQL, Tableau, and Power BI.
He has hands-on experience in analyzing real-world datasets, conducting exploratory data analysis (EDA), and creating impactful visualizations to derive actionable insights. Anuranj has successfully completed an internship in medical image processing, demonstrating his ability to work with complex data and leverage advanced techniques like Graph Attention Networks (GAT) to extract meaningful features.
Eager to continuously learn and grow, Anuranj is actively pursuing opportunities to apply his skills in professional environments. His proactive nature, technical proficiency, and ability to work collaboratively make him a valuable asset for data-driven roles.
Performed data cleaning and EDA on the Titanic dataset using Python to identify trends, patterns, and variable relationships.
Analyzed traffic accident data to identify hotspots and assess factors like road conditions and weather.
Visualized findings with Python.
Analyzed and visualized social media sentiment to understand public opinions on topics or brands.
Built a decision tree classifier using the Bank Marketing dataset to predict customer purchases based on demographic and behavioral data.
Performed data cleaning and EDA on the Titanic dataset using Python, Analyzed traffic accident data to identify hotspots and assess factors like road conditions and weather, Analyzed and visualized social media sentiment, Built a decision tree classifier using the Bank Marketing dataset to predict customer purchases based on demographic and behavioral data
Conducted extensive research on methodologies and technologies in disease detection and deep learning.
Managed the preprocessing of chest X-ray data, ensuring the dataset was clean and ready for analysis.
Applied advanced deep learning techniques, including CNN, VGG16, GCN, and GAT, for multiclass disease classification.
Assessed model performance using various metrics to ensure accuracy and reliability of classification results.
Prepared comprehensive reports detailing findings and outcomes of experiments.
Presented results effectively.
Conducted extensive research on methodologies and technologies in disease detection and deep learning, Managed the preprocessing of chest X-ray data, Applied advanced deep learning techniques for multiclass disease classification, Assessed model performance using various metrics, Prepared comprehensive reports detailing findings and outcomes, presented results effectively
Served as an NSS volunteer.
Assisted in organizing and coordinating various outreach programs.
Developed leadership skills.
Developed teamwork.
Developed community service.
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