Data Scientist and Machine Learning Engineer with hands-on experience in data analysis, predictive modeling, and deploying machine learning solutions.
Passionate about solving real-world problems with data and building portfolio-ready machine learning applications.

I specialize in transforming raw data into actionable insights and building end-to-end machine learning applications that solve real-world business problems.

Currently, I am focused on strengthening my technical expertise in advanced data analysis, machine learning optimization, and deployment workflows, while developing practical projects to showcase my skills.

Career Goal: Seeking internship/full-time roles in Data Science & Machine Learning to contribute to impactful projects.

• Applying advanced data analysis and visualization techniques to real-world datasets
• Developing and optimizing machine learning algorithms for practical problems
• Model evaluation, performance improvement, and feature engineering
• End-to-end ML model deployment and production workflows

Education:

• Intermediate (Completed)
• Associate Degree in Science (In Progress)

Certifications:

• Discover the Art of Prompting – Coursera
• Machine Learning Statistical Foundations - WOLFARM
• Career Essentials in GitHub - GitHub

Predicts whether water is safe for drinking using water quality parameters.

Key Work:

• Data cleaning and preprocessing
• Classification model development and evaluation
• Built a web interface for water safety prediction

Impact / Metrics:

• Accuracy: 70%
• Precision / Recall: 0.88 / 0.90

Technologies Used: Python, Pandas, Scikit-learn, Streamlit, HTML, CSS

Repository: Water Quality Data Analysis & Prediction

Live Demo: Live Demo

AI-powered loan approval prediction system with explainable AI.

Key Work:

• Trained ML models (Random Forest, XGBoost, LightGBM)
• Implemented SHAP & LIME for predictions
• Built Flask web app with authentication & admin dashboard

Impact: ~82% Accuracy, 0.89 Recall, 5-Fold CV

Tech: Python, Flask, Scikit-learn, XGBoost, LightGBM, SHAP, LIME, SQLite, HTML, CSS, JavaScript

Repo: LoanIQ — AI Loan Approval Prediction

ML-based web app that recommends job roles from resume content using NLP.

Key Work:

• Preprocessed resume & job description data
• Built an NLP-based job recommendation system
• Developed an interactive Streamlit web app

Impact: Improved job-role matching using similarity scoring

Tech: Python, Pandas, Scikit-learn, NLP, Streamlit

Repo: Resume Job Recommender

Live Demo: Live Demo

Predicts the likelihood of diabetes using medical attributes.

Key Work:

• Data cleaning and preprocessing
• Classification model development and evaluation
• Built a web interface for user input

Impact / Metrics:

• Accuracy: 73%
• Precision / Recall: 0.91 / 0.92

Technologies Used: Python, Pandas, Scikit-learn, HTML, CSS

Repository: Diabetes Prediction Web App

Analyzes medical text data using Natural Language Processing techniques.

Key Work:

• Medical text cleaning and preprocessing
• NLP model development and evaluation
• Built a web interface for medical text analysis

Impact / Metrics:

• Accuracy: 84%
• Precision / Recall: 0.86 / 0.96

Technologies Used: Python, Pandas, Scikit-learn, NLTK, Flask, HTML, CSS

Repository: Medical NLP Analyzer

Live Demo: