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Key Skills

Software

Other

Top Subject Matter

Machine learning for spam detection (health/health-tech adjacent chatbot ecosystem)

Health-tech ML prototype (hackathon)

Top Data Types

Text

Top Task Types

Classification

Question Answering

Freelancer Overview

AI & Cloud Intern — Edunet Foundation (with IBM & AICTE). Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include IBM Cloud and Other. Education includes Master of Computer Applications, Noida Institute of Engineering & Technology (NIET) (2024) and Bachelor of Computer Applications, Noida Institute of Engineering & Technology (NIET) (2024). AI-training focus includes data types such as Text and labeling workflows including Classification and Question Answering.

Labeling Experience

Participant – Hackathon 3.0, Maharishi University

OtherTextQuestion Answering

Developed an ML-driven health prototype in a hackathon context by designing backend logic and connecting ML predictions to a user-facing interface. The project focused on translating learned model outputs into consumable recommendations and interactions for health-oriented users. This included building an end-to-end pipeline where text-based inputs could be mapped to predicted health-related outputs. • Designed backend logic and integrated ML prediction outputs • Built a health prototype within a strict 48-hour team sprint • Connected ML predictions to the user-facing interface • Delivered a working end-to-end prototype under time constraints

2025 - 2025

AI & Cloud Intern — Edunet Foundation (with IBM & AICTE)

TextClassification

Worked as an AI & Cloud intern building and deploying a spam email classifier using supervised ML. The work involved preparing inputs for model training, evaluating model performance, and supporting deployment workflows on IBM platforms. Outputs were used to classify email text into spam vs. non-spam categories for downstream application usage. • Built spam email classifier achieving over 95% accuracy • Performed EDA and model evaluation to improve classification quality • Supported model deployment workflow using IBM Watson Studio/IBM Cloud • Applied MLOps practices for end-to-end ML lifecycle support

2024 - 2024

Education

Work History