I'm a passionate Data Scientist with experience in a variety of technologies and frameworks.

I hold a B.Tech in Information Technology and an M.Tech in Data Science. I currently work as an SDET at Zensar Technologies, leveraging Appium and Selenium for automated testing. I am passionate about solving complex problems with data.

Languages: Python, Java

Data Science Libraries: XGBoost, LightGBM, Scikit-Learn

Testing Tools: Selenium, Appium, TestNG

Frameworks: Ensemble Learning, Predictive Modelling Other Skills: Automation Testing, Data Visualization, Flutter

1. AI-Based Agriculture Recommendation System for Farmers
   Springer, Lecture Notes in Networks and Systems
   Read Chapter

2. Medical Mask Detection Using Various CNN Models
   IEEE Xplore, 2021 International Conference on System, Computation, Automation and Networking (ICSCAN)
   View Paper

3. Deep Learning-Based Recommendation System: A Survey
   International Journal of Innovative Science and Research Technology (IJISRT)
   Access Survey

1. ItineraryGenius
   A personalized travel assistant powered by generative AI. It crafts unique, detailed, and visually engaging travel itineraries based on user preferences, budget, and travel style. Features include AI-generated imagery, budget analysis, and exportable itineraries.

2. NalamAI
   An AI-powered health assistant offering multilingual, culturally tailored health advice. It supports voice interaction, symptom analysis via Gemini, and retrieval-augmented generation for real-time medical guidance.

3. LearnBuddiApp
   A comprehensive educational platform built with Flutter and Firebase. It supports course management, real-time updates, personalized learning paths, and integrated admin-student communication.

4. Ensemble XGBoost & LightGBM for Crop Yield Prediction
   A stacking ensemble model using optimized XGBoost and LightGBM to predict crop yields with improved accuracy and performance.

5. Plant Disease Detection Using Ensemble Learning
   Applied ensemble learning techniques to identify plant diseases with high precision, contributing to smarter agricultural diagnostics.

6. Stock Rate Predictor
   A deep learning project using LSTM neural networks to predict stock prices. Achieved strong performance with low error rates and includes data preprocessing, model optimization, and visualization.

REPOS :: https://github.com/prakash888kp?tab=repositories

📫 How to Reach Me

Twitter: @prakash888kp

Email: prakash888kp@yahoo.com