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 (Pursuing)

Certifications:

• Discover the Art of Prompting – Coursera
• Machine Learning Statical 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

Predicts whether a loan application will be approved.

Key Work:

• Data cleaning, feature engineering, and training classification algorithms
• Developed a web application for real-time prediction

Impact / Metrics:

• Model Accuracy: 89%

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

Repository: Loan Approval Prediction

A machine learning-based web application that matches resumes with relevant job roles using natural language processing and similarity techniques.

Key Work:

• Data preprocessing, text cleaning, and feature extraction from resumes and job descriptions
• Built a recommendation system using NLP techniques for job matching
• Developed an interactive web interface for uploading resumes and getting job suggestions

Impact / Metrics:

• Improved accuracy in matching relevant job roles based on resume content
• Better alignment between candidate skills and job requirements using similarity scoring

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

Repository: 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: