About
Highly motivated Post Graduate Student pursuing M.Tech in Data Science, with a Bachelor's in AI and Machine Learning. Possesses a strong foundation in developing and optimizing intelligent systems, evidenced by projects in explainable AI, deep learning, and natural language processing, consistently achieving high accuracy and delivering actionable insights.
Work
Future of Loan Approvals using Explainable AI
|AI/ML Developer
Remote, India, India
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Summary
Developed an intelligent loan approval system leveraging Random Forest and SHAP for transparent, high-accuracy predictions and interpretable decision-making.
Highlights
Developed an intelligent loan approval system using Random Forest, achieving 95% accuracy in loan status prediction and 90% accuracy in identifying rejection reasons from a 20,000+ application dataset.
Integrated SHAP (SHapley Additive exPlanations) for model interpretability, enabling transparent decision-making by quantifying each feature's contribution to loan approval/rejection predictions.
Built a user-friendly GUI application with Python's Tkinter, empowering non-technical users to upload datasets, train models, and visualize SHAP explanations through interactive plots.
Sudoku Solver
|Java Developer
Remote, India, India
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Summary
Created an efficient Sudoku solving application in Java, utilizing backtracking and OOP principles for optimized performance and maintainability.
Highlights
Developed a Sudoku solving application using Java, implementing backtracking and recursion algorithms to efficiently solve complex puzzles.
Utilized Object-Oriented Programming (OOP) principles to design a modular and maintainable codebase, ensuring clear separation of concerns and component reusability.
Optimized the backtracking algorithm to significantly improve performance, handling complex puzzles and reducing computation time.
Land Use Classification
|Deep Learning Engineer
Remote, India, India
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Summary
Developed a deep learning system for agricultural land use classification using EuroSAT imagery, achieving high accuracy through advanced model implementation.
Highlights
Developed a deep learning-based system for classifying agricultural land use from EuroSAT satellite imagery.
Implemented and compared models including Logistic Regression, Sequential Neural Networks, and CNNs (VGG16, ResNet34) using FastAI and TensorFlow, achieving up to 96.57% accuracy.
Enhanced model performance through fine-tuning and data augmentation, supporting sustainable agriculture applications.
Twitter Sentimental Analysis
|NLP Engineer
Remote, India, India
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Summary
Developed a sentiment analysis pipeline using Python, NLP, and LSTM networks to extract actionable insights from social media trends.
Highlights
Developed a sentiment analysis pipeline using Python, Natural Language Processing (NLP), and Long Short-Term Memory (LSTM) networks.
Designed and trained LSTM-based models for sentiment classification, achieving high accuracy in detecting positive, negative, and neutral sentiments.
Enabled actionable insights from social media trends, aiding business decision-making and public opinion analysis.
Online, India, India
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Summary
Completed an intensive AI/ML externship, gaining practical experience in machine learning model development and data-driven forecasting.
Highlights
Completed an online course focusing on Artificial Intelligence and Machine Learning, gaining hands-on experience with ML models, data preprocessing, and AI applications in various domains.
Built a predictive model to forecast Walmart store sales using historical data, seasonal trends, and promotional events.
Applied machine learning algorithms to improve forecasting accuracy and support data-driven inventory decisions.
Education
IIT Palakkad
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M.Tech
Data Science
VIT-AP University
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Bachelors of Technology
CSE-Artificial Intelligence and Machine Learning
Sri Bhavishya Educational Institutions
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Intermediate
Intermediate
Languages
English
Skills
Programming Languages
Python, Java, SQL.
Machine Learning & AI
Machine Learning, Deep Learning, Natural Language Processing (NLP), Explainable AI (XAI), Random Forest, SHAP, LSTM, VGG16, ResNet, FastAI, TensorFlow.
Tools & Frameworks
Tkinter, Git.
Data Analysis
Data Preprocessing, Data Visualization, Forecasting.
Soft Skills
Problem Solving, Team Leadership, Staff Management.