AI Engineer Trainee passionate about Machine Learning, Data Science, and Generative AI. Skilled in building real-world projects using Python, NLP, and modern AI
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Datamites
Data Scientist
June 17, 2026 – Present
Student-Performance-Prediction-Using-Gaussian-Naive-Bayes
June 14, 2026 – Present
A machine learning project that predicts student Pass/Fail outcomes using the Gaussian Naive Bayes algorithm based on Attendance, Study Hours, and Previous Marks. Includes EDA, model evaluation, probability-based predictions, and an interactive Streamlit dashboard.
View ProjectWine-Quality-Analysis-and-Visualization-Using-Principal-Component-Analysis-PCA-
June 11, 2026 – Present
Developed an interactive Flask-based dashboard for wine quality analysis using Principal Component Analysis (PCA). The application performs dimensionality reduction, visualizes feature relationships through Chart.js, and provides insights into wine characteristics using an intuitive web interface.
View ProjectMedical-Chatbot-using-Retrieval-Augmented-Generation-and-LangChain
June 11, 2026 – Present
Medical Chatbot using RAG and LangChain Developed an AI-powered medical chatbot using Retrieval-Augmented Generation (RAG) and LangChain. Integrated a medical knowledge base for accurate, context-aware responses, enabling efficient healthcare information retrieval and question answering.
View ProjectOlympics-Dataset-Data-Cleaning-Standardization-Project
May 24, 2026 – Present
A structured end-to-end data cleaning project on a raw Olympics dataset covering 800+ athlete records. Resolves duplicates, missing values, inconsistent country codes, medal labels, name formats, and invalid ranges — producing a fully standardized, analysis-ready CSV with a documented Jupyter notebook.
View ProjectTechnology-Lookup-Data-Cleaning-Tool
May 24, 2026 – Present
Technology Lookup & Data Cleaning Tool is a smart normalization engine that resolves messy, inconsistent technology names — abbreviations, aliases, and typos — into clean, canonical entries enriched with category metadata. Supporting 100+ mappings across languages, frameworks, databases, DevOps tools, cloud platforms, and ML libraries.
View ProjectIPL-Match-Winner-Predictor-using-Random-Forest
May 19, 2026 – Present
Built a machine learning project to predict IPL match winners using match conditions like teams, venue, toss, and player performance. Implemented the Random Forest Classifier for accurate predictions and developed an interactive web interface for real-time match outcome analysis.
View ProjectAI-Air-Canvas-Real-Time-Writing-Using-Computer-Vision
April 22, 2026 – Present
Developed an AI-powered Air Canvas using OpenCV and MediaPipe that enables real-time drawing using hand gestures. The system tracks finger movements through a webcam to create a touchless digital writing experience.
View ProjectStationery-Management-System
March 13, 2026 – Present
Developed a web-based DBMS inventory management system using PHP, HTML, CSS, and MySQL with features like user authentication, stock tracking, and report generation. Designed a responsive interface with automated low-stock alerts and notifications to improve inventory control, operational efficiency, and user experience.
View ProjectAutomating-Data-Cleansing-for-Healthcare-Records-using-NLP
March 13, 2026 – Present
Developed an automated NLP pipeline using Python to clean and standardize unstructured healthcare data through error detection, imputation, and terminology alignment. Improved data accuracy and reduced manual processing time, enhancing data readiness for AI-driven analysis and clinical decision-making.
View ProjectFacial-Analysis-Powered-Virtual-Healthcare
March 13, 2026 – Present
Developed a virtual healthcare system for depression detection using multi-modal emotion analysis. Implemented CNN with Haar Cascade for facial emotion recognition and TF-IDF with Multinomial Naive Bayes for voice sentiment analysis, integrated with an emotion-aware chatbot to provide real-time emotional assessment and personalized
View ProjectCultural Fit Analysis
The candidate's projects are predominantly personal and academic, showcasing a strong drive for learning and applying new technologies in the data science domain. The diversity of projects, from predictive modeling to computer vision and NLP, indicates a broad interest and adaptability. However, the lack of professional experience beyond a current role with no specified start date makes it difficult to fully assess cultural fit in a corporate environment. The projects align well with a Data Scientist role, demonstrating initiative and problem-solving skills.
Soft Skills & Operational Fit
The candidate's project descriptions suggest an ability to work on diverse problems and integrate various technologies. However, without specific psychometric or English test results, it is difficult to assess soft skills like communication clarity, work attitude, stress handling, or team collaboration. The project descriptions are clear and well-structured, indicating good written communication.