Pratham K.

Key Skills

Software

Don't disclose

Top Subject Matter

engineering

food and fashion

e-commerce product categorization

Top Data Types

Image

Text

Top Task Types

Classification

Question Answering

Freelancer Overview

AI System Developer and Image Data Labeler. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include analytical, conceptual and strategical problem solving. Education includes Bachelor of Technology, Indian Institute of Technology Delhi. AI-training focus includes data types such as Image and Text and labeling workflows including Classification and Question Answering.

Labeling Experience

Information Retrieval Data Labeler and Annotator

TextQuestion Answering

I worked on a custom information retrieval tool integrating OpenAI APIs and large language models (LLMs). The role included creating structured question-answer pairs and annotating relevant text segments to train the retrieval system. I evaluated the accuracy of extracted results and improved context-aware responses through ongoing annotation. • Generated question-answer pairs for supervised LLM training. • Annotated large text corpuses for relevance in information retrieval. • Tested and validated context accuracy in responses from AI models. • Enhanced tool precision via iterative manual labeling and feedback.

2024 - 2024

NLP Project Data Labeler

TextClassification

I developed a sentiment analysis model to classify movie reviews as positive or negative using natural language processing (NLP). The work included data cleaning, tokenization, and the manual annotation of sample text reviews to build and validate training sets. I applied embedding and labeling techniques to enhance the accuracy of the AI models. • Built and labeled a dataset of movie reviews for sentiment classification. • Preprocessed text using tokenization, lemmatization, and word frequency analysis. • Used TF-IDF methods and conducted manual annotation for initial ground-truth labeling. • Evaluated and refined labeled data sets for model accuracy and reliability.

2024 - 2024

Education

Work History