Summary
I am a BS Computer Science student and Machine Learning Developer with a strong passion for Machine Learning and Generative AI. With machine learning, data science, and generative AI expertise, I have completed various projects, including the HR Attrition Predictor (97.96% accuracy) and the Tweet Virality Predictor. My experience as a Machine Learning Fellow at Bytewise Limited and GDGoC has honed my problem-solving skills and technical proficiency, enabling me to develop innovative solutions to complex challenges.
Education
Relevant Courses: Programming Fundamentals, OOP, Data Structures, Design and Analysis of Algorithms, Databases, Operating Systems, Computer Networks, Software Engineering, Compiler Construction, Theory of Automata, Artificial Intelligence, Data Analysis and Visualization, Information Security, Cloud Computing
Experience
- Developing Python programming skills through weekly assignments and real-world application development
- Created a Student Report Card Generator that produces reports in multiple formats (Text, Word, PDF)
- Working on hands-on Machine Learning curriculum, gaining experience in building and deploying models
- Key tasks include Data Preprocessing, EDA, Supervised ML Models, Unsupervised ML Models, and Capstone Projects
- Developing an HR Attrition Predictor to identify employee turnover factors and display insights through a Streamlit app
- Worked with machine learning techniques including clustering, neural networks, and predictive modeling
- Completed projects like customer churn prediction and Formula 1 race outcomes prediction
- Built web applications with Flask for model deployment and gained experience in data processing and analysis
Projects
- Machine Learning
- Streamlit
- Decision Tree Classifier
- Developed a Machine Learning-powered Streamlit app that predicts employee attrition with 97.96% accuracy
- Implemented workforce pattern visualization and actionable insights through a Decision Tree Classifier
- Python
- Random Forest
- Logistic Regression
- Created a machine learning application that predicts tweet virality using Random Forest and Logistic Regression
- Implemented content analysis, sentiment analysis, and timing features, achieving 85% accuracy
- Python
- Flask
- Machine Learning
- Developed a Flask web application that predicts customer churn using machine learning
- Implemented data preprocessing, exploratory analysis, and real-time predictions with multiple model implementations
- Python
- PDF Generation
- Built a comprehensive system for generating student report cards in multiple formats (Text, Word, PDF)
- Implemented automated grade calculation and customizable report templates
Technical Skills
Primary Skills
- Python
- Machine Learning
- Data Preprocessing
- Exploratory Data Analysis
- Data Analysis
- Supervised Learning
- Unsupervised Learning
- Generative AI
- Large Language Models (LLM)
- Prompt Engineering
- Front-End Development
- Flask
Additional Skills
- HTML5
- CSS
- Git
- GitHub
- Microsoft Office
- Postman API
- Data Structures
- Algorithms
Certifications & Achievements
Certifications
- AI For Everyone, DeepLearning.AI, Mar. 2025
- Machine Learning Fellowship, Bytewise Limited, Sep. 2024
- AI Fundamentals, DataCamp, Aug. 2024
- ChatGPT Fundamentals, DataCamp, Aug. 2024
- Postman API Fundamentals Student Expert, Canvas Credentials (Badgr), Aug. 2024
- Prompt Engineering for ChatGPT, Vanderbilt University, Aug. 2023
- Programming For Everybody (Python), University of Michigan, Jan. 2023
Achievements
- Head of Skill Development Wing, NSSI Society Namal
- Beta Microsoft Learn Student Ambassador (2024 - Present)
- Completed Hacktoberfest 2024 with accepted PRs
- Campus Ambassador: GSSoC 2024 (4th, 260+ reg.), DEN Coding Cup (3rd, 28+ reg.), Tech Fest Gala 2024, HackX PSIFI XVI (5 reg, PSIFI Hoodie Winner), COSMICON
- 1st Place, Python Quiz, TechTrivium
- 1,500+ LinkedIn followers
- Google Cloud AI Study Jam (Season 6), 31 badges completed