DIVYA K

About

Motivated and enthusiastic B.Tech Artificial Intelligence and Data Science student seeking an entry-level opportunity to apply technical skills, learn from industry professionals, and contribute effectively to organizational goals. Interested in continuous learning and hands-on work in data science and machine learning.

Education

• B.Tech
  Mahendra Engineering College (Autonomous)
  Artificial Intelligence & Data Science

Skills

• SQL <3 months
• CSS <3 months
• Deep Learning <3 months
• HTML <3 months
• Python <3 months
• Machine Learning <3 months
• Data Science <3 months
• Java <3 months
• JavaScript <3 months
• Matplotlib <3 months
• NumPy <3 months
• Streamlit <3 months
• OpenCV <3 months
• TensorFlow <3 months
• Operating Systems <3 months
• CNN (Convolutional Neural Network) <3 months
• XML <3 months
• GPS (RTK) <3 months
• Mediapipe <3 months
• Advanced DBMS <3 months
• Generative AI (ChatGPT, Copilot, Gemini) <3 months

Tools / apps / platforms

• Git <3 months
• GitHub <3 months
• Microsoft Excel <3 months
• Microsoft Power BI <3 months
• Tableau <3 months
• VS Code <3 months

Projects

• Speech Emotion Detection System
  Python, Streamlit, TensorFlow, NumPy, Matplotlib

  Built an end-to-end speech emotion recognition system using deep learning. Processed real-time audio input and extracted features for emotion classification. Achieved accurate predictions across multiple emotion classes (happy, sad, angry, etc.).

• YOLO-Based Real-Time Pothole Detection and IoT Reporting System
  Python, YOLOv8, Deep Learning, OpenCV, GPS

  Developed a real-time pothole detection model using YOLOv8. Integrated GPS-based location tracking for automated reporting. Improved detection accuracy through image preprocessing and model training. Improved road maintenance support through automated detection and reporting.

• Sign Language to Text & Text to Sign Language Converter
  Python, MediaPipe, CNN, TensorFlow, Streamlit

  Developed a bidirectional system to convert sign language gestures into text and text into sign language output. Used OpenCV for real-time hand gesture detection and image preprocessing. Trained machine learning models for accurate gesture recognition.

🏆 Achievements & awards

• Paper selected for IEEE Conference

  YOLO-Based Real-Time Pothole Detection and IoT Enabled Reporting with GPS Localization.