Engineered a groundbreaking Flood Relief System as a final year project, leading a dynamic 3-member team. Expertly integrated MERN (MongoDB, Express.js, React, Node.js), Flask, Power BI, and Python for full-stack development. Leveraged machine learning for data-driven insights and implemented a chatbot using NLP techniques. Demonstrated proficiency in efficient data management, insightful Power BI visualization, and introduced an intelligent chatbot for transformative flood relief management.
Engineered a groundbreaking Flood Relief System as a final year project, leading a dynamic 3-member team. Expertly integrated MERN (MongoDB, Express.js, React, Node.js), Flask, Power BI, and Python for full-stack development. Leveraged machine learning for data-driven insights and implemented a chatbot using NLP techniques. Demonstrated proficiency in efficient data management, insightful Power BI visualization, and introduced an intelligent chatbot for transformative flood relief management.
Stress Identification Using IIOT integrates MAX30102 for heart rate monitoring, DHT11 for temperature sensing, and HC-05 Bluetooth module for data transmission. Collected data is published to MQTT for real-time analysis. The project includes a frontend interface for interactive visualization and detailed stress analysis.
Developed a comprehensive "Restaurant-Recommendation-Chatbot" in Python, demonstrating proficiency in NLP, recommendation systems, and conversational UI. The project encompasses robust data preprocessing, feature extraction, and user-friendly interactions, ensuring seamless experiences. Thorough testing and iterative development were undertaken, and the system allows users to save personalized recommendations based on their preferences.
Developed a comprehensive "Restaurant-Recommendation-Chatbot" in Python, demonstrating proficiency in NLP, recommendation systems, and conversational UI. The project encompasses robust data preprocessing, feature extraction, and user-friendly interactions, ensuring seamless experiences. Thorough testing and iterative development were undertaken, and the system allows users to save personalized recommendations based on their preferences.
Engineered a groundbreaking Flood Relief System as a final year project, leading a dynamic 3-member team. Expertly integrated MERN (MongoDB, Express.js, React, Node.js), Flask, Power BI, and Python for full-stack development. Leveraged machine learning for data-driven insights and implemented a chatbot using NLP techniques. Demonstrated proficiency in efficient data management, insightful Power BI visualization, and introduced an intelligent chatbot for transformative flood relief management.
Conducted an in-depth research study on customer retention utilizing machine learning techniques. Performed a thorough literature review and implemented diverse models, such as XGBoost, Logistic Regression, Random Forest, and Decision Tree, for predicting customer churn. Demonstrated expertise in model evaluation, highlighting XGBoost's superior performance with an accuracy of 0.80 and robust discriminative power, evidenced by an AUC of 0.84 within a 3-member team.
Conducted an in-depth research study on customer retention utilizing machine learning techniques. Performed a thorough literature review and implemented diverse models, such as XGBoost, Logistic Regression, Random Forest, and Decision Tree, for predicting customer churn. Demonstrated expertise in model evaluation, highlighting XGBoost's superior performance with an accuracy of 0.80 and robust discriminative power, evidenced by an AUC of 0.84 within a 3-member team.
Conducted an in-depth research study on customer retention utilizing machine learning techniques. Performed a thorough literature review and implemented diverse models, such as XGBoost, Logistic Regression, Random Forest, and Decision Tree, for predicting customer churn. Demonstrated expertise in model evaluation, highlighting XGBoost's superior performance with an accuracy of 0.80 and robust discriminative power, evidenced by an AUC of 0.84 within a 3-member team.
Conducted extensive research on breast cancer classification using machine learning techniques. Executed a comprehensive literature review and implemented algorithms for effective cancer diagnosis. Demonstrated expertise in model evaluation and performance assessment
Conducted extensive research on breast cancer classification using machine learning techniques. Executed a comprehensive literature review and implemented various algorithms for effective cancer diagnosis. Demonstrated expertise in model evaluation and performance assessment
Conducted in-depth research and implemented a robust Convolutional Neural Network (CNN) for fruit recognition, addressing the challenge of diverse intra-class forms, colors, and textures. Successfully applied deep learning techniques to automate fruit classification, contributing to accessibility for children, visually impaired individuals, and enhancing self-checking supermarkets. Achieved high accuracy, surpassing 95%, through meticulous model evaluation, comparative analysis, and innovative configurations within a 3-member team.
Conducted in-depth research and implemented a robust Convolutional Neural Network (CNN) for fruit recognition, addressing the challenge of diverse intra-class forms, colors, and textures. Successfully applied deep learning techniques to automate fruit classification, contributing to accessibility for children, visually impaired individuals, and enhancing self-checking supermarkets. Achieved high accuracy, surpassing 95%, through meticulous model evaluation, comparative analysis, and innovative configurations within a 3-member team.
Conducted in-depth research and implemented a robust Convolutional Neural Network (CNN) for fruit recognition, addressing the challenge of diverse intra-class forms, colors, and textures. Successfully applied deep learning techniques to automate fruit classification, contributing to accessibility for children, visually impaired individuals, and enhancing self-checking supermarkets. Achieved high accuracy, surpassing 95%, through meticulous model evaluation, comparative analysis, and innovative configurations within a 3-member team.
Led a collaborative 3-member team in the development of a Budget Control System. Spearheaded project scope definition, employed ReactJS for frontend, and integrated Unified Modeling Language (UML) for backend system modeling along with SQL. Innovatively incorporated market options, providing distinctive solutions for effective budget control.
Led a collaborative 3-member team in the development of a Budget Control System. Spearheaded project scope definition, employed ReactJS for frontend, and integrated Unified Modeling Language (UML) for backend system modeling along with SQL. Innovatively incorporated market options, providing distinctive solutions for effective budget control.
Led a collaborative 3-member team in the development of a Budget Control System. Spearheaded project scope definition, employed ReactJS for frontend, and integrated Unified Modeling Language (UML) for backend system modeling along with SQL. Innovatively incorporated market options, providing distinctive solutions for effective budget control.
I have demonstrated expertise in developing a specialized Restaurant Menu Scraper tool. By leveraging web scraping techniques, I automated the extraction of detailed menu data, including modifiers and prices, from restaurant website. This project underscores my proficiency in Python, web scraping, and data manipulation, showcasing a tangible impact on operational efficiency and data accuracy.
I have demonstrated expertise in developing a specialized Restaurant Menu Scraper tool. By leveraging web scraping techniques, I automated the extraction of detailed menu data, including modifiers and prices, from restaurant website. This project underscores my proficiency in Python, web scraping, and data manipulation, showcasing a tangible impact on operational efficiency and data accuracy.
During my Data Science Internship, I developed the 'Sentiment Analysis on Social Media Comments' project for SocialBuzz Inc., a fictional company. Leveraging Python, I applied NLP techniques with NLTK for preprocessing, TF-IDF for feature extraction, and Flask for API deployment. This project showcases my proficiency in seamlessly integrating technologies to deliver a robust sentiment analysis model, enabling the assessment of brand perception from social media comments
During my Data Science Internship, I developed the 'Sentiment Analysis on Social Media Comments' project for SocialBuzz Inc., a fictional company. Leveraging Python, I applied NLP techniques with NLTK for preprocessing, TF-IDF for feature extraction, and Flask for API deployment. This project showcases my proficiency in seamlessly integrating technologies to deliver a robust sentiment analysis model, enabling the assessment of brand perception from social media comments
During my Data Science Internship, I developed the 'Sentiment Analysis on Social Media Comments' project for SocialBuzz Inc., a fictional company. Leveraging Python, I applied NLP techniques with NLTK for preprocessing, TF-IDF for feature extraction, and Flask for API deployment. This project showcases my proficiency in seamlessly integrating technologies to deliver a robust sentiment analysis model, enabling the assessment of brand perception from social media comments
During my Data Science Internship, I conducted Exploratory Data Analysis (EDA) for TechElectro Inc., a fictional company. This involved unveiling valuable insights into customer preferences and behaviors, utilizing advanced data analysis techniques. The outcome contributed to effective customer segmentation, empowering optimized marketing strategies and fostering enhanced customer satisfaction through informed, data-driven decision-making.
During my Data Science Internship, I conducted Exploratory Data Analysis (EDA) for TechElectro Inc., a fictional company. This involved unveiling valuable insights into customer preferences and behaviors, utilizing advanced data analysis techniques. The outcome contributed to effective customer segmentation, empowering optimized marketing strategies and fostering enhanced customer satisfaction through informed, data-driven decision-making.
During my Data Science Internship, I conducted Exploratory Data Analysis (EDA) for TechElectro Inc., a fictional company. This involved unveiling valuable insights into customer preferences and behaviors, utilizing advanced data analysis techniques. The outcome contributed to effective customer segmentation, empowering optimized marketing strategies and fostering enhanced customer satisfaction through informed, data-driven decision-making.
Independently curated the Power BI Projects Collection during my Data Science internship, showcasing a range of insightful dashboards that extract meaningful insights from diverse datasets. Applied expertise in data visualization and analysis to develop projects like Email Spam Classification, Bank Credit Scoring, and World's Biggest Data Breaches and Hacks. Demonstrated the ability to unravel complex patterns and deliver impactful visualizations for informed decision-making.
Independently curated the Power BI Projects Collection during my Data Science internship, showcasing a range of insightful dashboards that extract meaningful insights from diverse datasets. Applied expertise in data visualization and analysis to develop projects like Email Spam Classification, Bank Credit Scoring, and World's Biggest Data Breaches and Hacks. Demonstrated the ability to unravel complex patterns and deliver impactful visualizations for informed decision-making.
Independently curated the Power BI Projects Collection during my Data Science internship, showcasing a range of insightful dashboards that extract meaningful insights from diverse datasets. Applied expertise in data visualization and analysis to develop projects like Email Spam Classification, Bank Credit Scoring, and World's Biggest Data Breaches and Hacks. Demonstrated the ability to unravel complex patterns and deliver impactful visualizations for informed decision-making..
Developed a Library Management System utilizing SQL and C# in a team of three, streamlining functionalities such as Catalog, User/Admin Login and more. Demonstrated effective collaboration, project management, and database design skills to improve library services and user experience.
Developed a Library Management System utilizing SQL and C# in a team of three, streamlining functionalities such as Catalog, User/Admin Login and more. Demonstrated effective collaboration, project management, and database design skills to improve library services and user experience.
Skills
Programming Languages: Python (Advanced), C++ (Advanced), C (Intermediate), SQL (Advanced), HTML (Intermediate), CSS (Intermediate), JavaScript (Intermediate)
Frameworks & Technologies: MERN Stack (Intermediate), Data (Scraping/Analysis/Visualization) (Advanced), Machine Learning (Intermediate), Flask (Intermediate), PySpark (Intermediate), Arduino Programming (Intermediate), Power BI (Intermediate)
Version Control & Collaboration: Git (Intermediate), LaTeX (Intermediate), Team Collaboration (Advanced), Time Management (Advanced), Leadership (Intermediate), Adaptability (Advanced), Communication (Intermediate), Attention to Detail (Advanced)