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MadhukarSaiBabu/README.md

💫 About Me:

👋 About Me

Hi there! I'm Madhukar Sai Babu Gadde, a passionate and driven Computer Science student specializing in Big Data Analytics at SRM University, AP. I enjoy exploring the intersection of data science, software development, and real-world problem solving.

🔍 I’ve worked on diverse projects—from predicting house prices using machine learning to analyzing aviation trends using Hadoop MapReduce, Hive, and R. My passion for data-driven insights is also reflected in my research on coral reef protection using computer vision and spatial data mining for earthquake significance classification, published in IEEE and Springer.

💻 I’m also experienced in full-stack web development with HTML, CSS, JavaScript, Node.js, Express, and MongoDB, and have a growing interest in cybersecurity, showcased through hands-on projects like ethical keylogger simulations.

📊 Tools and Technologies I work with:

Languages: Python, C, SQL
Libraries & Frameworks: Scikit-learn, Bokeh, Hive, MapReduce
Tools: Power BI, MS Office, MySQL, Canva
Certifications: Cisco Data Analytics, ServiceNow Fundamentals

🚀 I’m always eager to collaborate on impactful projects, contribute to open-source, and learn something new every day. Let’s connect!

🌐 Socials:

LinkedIn email

💻 Tech Stack:

C C++ HTML5 Java JavaScript R Python Netlify Anaconda Apache Spark Apache Kafka Apache Hadoop Apache Hive Express.js NodeJS MySQL NumPy Pandas Matplotlib PyTorch scikit-learn TensorFlow

📊 GitHub Stats:



🏆 GitHub Trophies

✍️ Random Dev Quote

Popular repositories Loading

  1. Spatial-Data-Mining-for-Earthquake-Significance-Classification Spatial-Data-Mining-for-Earthquake-Significance-Classification Public

    This study applies spatial data mining to classify earthquake significance using ML models. Random Forest and Bagging outperformed others in accuracy, precision, recall, and F1-score, proving effec…

    Jupyter Notebook 1

  2. ML-for-Workforce-Analytics-Sales-Forecasting-Segmentation-Sentiment-Analysis ML-for-Workforce-Analytics-Sales-Forecasting-Segmentation-Sentiment-Analysis Public

    Implemented machine learning across HR, Sales, Marketing, and PR to improve decision-making. Used models like XGBoost, Prophet, LSTM, clustering, and NLP to enhance retention, forecasting, segmenta…

    Jupyter Notebook 1

  3. Real-time-Coral-Reefs-Monitoring-and-Protection-using-Computer-Vision-A-Case-Study-on-COTS-Detection Real-time-Coral-Reefs-Monitoring-and-Protection-using-Computer-Vision-A-Case-Study-on-COTS-Detection Public

    This project uses YOLO V5, a real-time object detection model, to identify Crown-of-Thorns Starfish threatening coral reefs. Leveraging machine learning and computer vision aids reef restoration by…

    1

  4. Enhancing-Coral-Reef-Restoration-with-YOLOv8-Real-Time-Monitoring-Using-Deep-Learning Enhancing-Coral-Reef-Restoration-with-YOLOv8-Real-Time-Monitoring-Using-Deep-Learning Public

    This study uses YOLOv8, RNNs, and LSTMs to detect threats like COTS and predict reef health trends, enabling real-time monitoring and smarter restoration strategies to support long-term resilience …

    1

  5. Aviation-Trend-Analysis-using-MapReduce-and-R Aviation-Trend-Analysis-using-MapReduce-and-R Public

    Developed a data-driven solution leveraging Hadoop MapReduce, Hive, and R to analyze air travel data. Identified trends in passenger volume, route utilization, and peak travel periods, providing ac…

    1

  6. House-Price-prediction House-Price-prediction Public

    This project aims to build a predictive model using ML and regression to estimate house prices, identify key value drivers, and support informed decision-making for stakeholders in real estate tran…

    Jupyter Notebook