Ms. Khan

Key Skills

Software

CVAT

Img Lab

Kili Technology

Labelbox

Other

Top Subject Matter

NER Classification

Sentiment Analysis

Text summarization

Top Data Types

Document

Image

Text

Top Label Types

Bounding Box

Entity Ner Classification

Object Detection

Relationship

Text Summarization

Freelancer Overview

Detail-oriented and experienced Data Annotation Specialist with over 6 years of progressive roles in data annotation and quality control. Proven expertise in Named Entity Recognition (NER), Relationship Extraction (RE), and various annotation projects, contributing to the development of accurate datasets for machine learning applications. Skilled in project management, quality assessment, and utilizing annotation tools to ensure the efficiency and precision of AI/ML workflows.

Labeling Experience

NER Classification

OtherTextBounding BoxPolygon

. John Snow Labs NLP Lab - Annotation Tool ● Project Overview: ● Utilized the Annotation Lab within John Snow Labs NLP Lab, focusing on text, PDF, and image annotation. ● Managed projects efficiently through the Project Dashboard, assigned tasks, and roles, and initiated effective project cloning strategies. ● Key Responsibilities: ● Initiated projects by selecting content types for annotation and customized annotation configurations based on project requirements. ● Provided clear and concise annotation guidelines, ensuring team adherence to specific criteria. ● Achievements: ● Demonstrated flexibility in customizing configurations, optimizing AI/ML workflows. ● Maintained organizational efficiency and accuracy in task assignments, ensuring successful collaboration among team members

. John Snow Labs NLP Lab - Annotation Tool ● Project Overview: ● Utilized the Annotation Lab within John Snow Labs NLP Lab, focusing on text, PDF, and image annotation. ● Managed projects efficiently through the Project Dashboard, assigned tasks, and roles, and initiated effective project cloning strategies. ● Key Responsibilities: ● Initiated projects by selecting content types for annotation and customized annotation configurations based on project requirements. ● Provided clear and concise annotation guidelines, ensuring team adherence to specific criteria. ● Achievements: ● Demonstrated flexibility in customizing configurations, optimizing AI/ML workflows. ● Maintained organizational efficiency and accuracy in task assignments, ensuring successful collaboration among team members

2022 - 2023

Image Annotation

Kili TechnologyImageBounding BoxPolygon

Project Overview: ● Utilized Kili Technology’s Image and Text Annotation Tool for annotating digital images to recognize and classify target objects related to organizations or brands. ● Focused on image classification, object recognition and detection, segmentation, semantic segmentation, and instance segmentation, with a primary emphasis on tagging organizations accurately. ● Key Responsibilities: ● Implemented comprehensive training and guidelines for annotators, ensuring accuracy and understanding of complex annotation tasks. ● Managed the annotation project through a dedicated process, addressing challenges related to timeline, team structure, task distribution, and quality management. ● Achievements: ● Successfully contributed to the training of machine learning models for object recognition and classification. ● Ensured accuracy and efficiency through meticulous project management, laying the foundation for successful model training.

Project Overview: ● Utilized Kili Technology’s Image and Text Annotation Tool for annotating digital images to recognize and classify target objects related to organizations or brands. ● Focused on image classification, object recognition and detection, segmentation, semantic segmentation, and instance segmentation, with a primary emphasis on tagging organizations accurately. ● Key Responsibilities: ● Implemented comprehensive training and guidelines for annotators, ensuring accuracy and understanding of complex annotation tasks. ● Managed the annotation project through a dedicated process, addressing challenges related to timeline, team structure, task distribution, and quality management. ● Achievements: ● Successfully contributed to the training of machine learning models for object recognition and classification. ● Ensured accuracy and efficiency through meticulous project management, laying the foundation for successful model training.

2019 - 2022

Data Labeller

OtherTextEntity Ner ClassificationText Summarization

The Named Entity Recognition (NER) project was a critical initiative within Natural Language Processing (NLP), specifically designed to identify and categorize entities in text. The focus was on the extraction of essential information from unstructured text, enhancing the understanding of specific entities. Key Responsibilities: ● Implemented NER methods to detect and categorize entities in text. ● Collaborated with a multidisciplinary team to define and customize entity categories, including Organization, Person, Location, Time, etc. ● Developed custom categories tailored to specific use cases such as Healthcare Terms and Programming Languages. Process and Significance: NER involved a systematic process of extracting and categorizing detected entities into predefined categories. The significance of NER lies in its pivotal role in extracting structured information from unstructured text, enabling applications in information retrieval, question answering, and document summarization.

The Named Entity Recognition (NER) project was a critical initiative within Natural Language Processing (NLP), specifically designed to identify and categorize entities in text. The focus was on the extraction of essential information from unstructured text, enhancing the understanding of specific entities. Key Responsibilities: ● Implemented NER methods to detect and categorize entities in text. ● Collaborated with a multidisciplinary team to define and customize entity categories, including Organization, Person, Location, Time, etc. ● Developed custom categories tailored to specific use cases such as Healthcare Terms and Programming Languages. Process and Significance: NER involved a systematic process of extracting and categorizing detected entities into predefined categories. The significance of NER lies in its pivotal role in extracting structured information from unstructured text, enabling applications in information retrieval, question answering, and document summarization.

2017 - 2021

Education

Work History