Ankita Narayankar

Computer Science Engineering student · Machine Learning, NLP & Computer Vision

Dharwad, Karnataka, India

@ankita_narayankar

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🎓 B.E. Computer Science Engineering at Jain College of Engineering and Technology, Hubli · Graduating 2027

About

Computer Science Engineering student with hands-on experience in machine learning, NLP, and computer vision. Has built classification models for fraud detection, resume screening, and plant disease detection, with a strong foundation in Python and data structures.

Experience

Data Science Intern

CodeC Technologies · Hybrid, India

Nov 2025 – Nov 2025

Built machine learning models and performed data preprocessing using Python.
Python Intern

Axile.X Group of Companies

Oct 2024 – Nov 2024

Developed Python applications and gained hands-on programming experience.

Education

B.E. Computer Science Engineering

Jain College of Engineering and Technology, Hubli · VTU

Computer Science Engineering · 2023 – 2027

Skills

3 to 6 months

Python

<3 months

C CSS Oop HTML Java NumPy React Flask SMOTE Pandas OpenCV Tf-Idf Networkx JavaScript OpenAI API scikit-learn Computer Vision Machine Learning Data Preprocessing Natural Language Processing Data Structures and Algorithms

Tools / apps / platforms

<3 months

Git GitHub VS Code Amazon Web Services AWS

Projects

Civic Track

React, JavaScript, HTML, CSS

Developed a web platform for reporting and tracking civic issues with a user-friendly interface.
Cloud Attendance System

HTML, CSS, AWS

Built a web-based smart attendance management application that stores and manages attendance records using cloud technology.
Credit Card Fraud Detection

Python, Pandas, Scikit-learn, SMOTE

Developed a fraud detection model on highly imbalanced transaction data, applying resampling techniques to improve recall on the minority (fraud) class.
Money Muling Detection System

Python, NetworkX, Pandas, Scikit-learn

Engineered features from transaction patterns and user behavior to flag potential money muling activity for early fraud detection. Applied machine learning techniques and data preprocessing to improve fraud detection accuracy.
AI-Based Resume Screening & Job Recommendation System

Python, Flask, NLP, TF-IDF, OpenAI API

Built an NLP pipeline to parse and score resumes against job descriptions, with a job recommendation module and automated interview-question generation.
Plant Disease Detection System

Python, OpenCV, scikit-learn

Built a computer vision model to classify plant diseases from leaf images, applying image preprocessing (augmentation, normalization) to improve generalization.

⚽ Extracurricular activities

RIFT ’26 Hackathon

Ranked in the top 20 among 1000+ teams for building a prototype solution under time constraints to demonstrate rapid problem-solving.
Intercollege Hack Arena

Secured 3rd place in a team-based development competition.

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