Nasir Zaman

Key Skills

Software

AWS SageMaker

Dataturk

Labelbox

Top Subject Matter

FOOD & BEVERAGE

LOGISTICS & SUPPLY CHAIN

GROCERS & RETAIL

Top Data Types

Image

Medical Dicom

Video

Top Label Types

Action Recognition

Classification

Data Collection

Emotion Recognition

Entity Ner Classification

Freelancer Overview

With extensive experience in data labeling and AI training data, I excel in annotating diverse datasets to empower machine learning models across various domains. Proficient in image, text, and audio annotation, I have contributed to numerous projects requiring precise labeling for tasks such as object detection, sentiment analysis, and speech recognition. Leveraging my expertise in tools like Labelbox and Amazon SageMaker Ground Truth, I ensure high-quality annotations that enhance model accuracy and performance. My background includes working on projects ranging from computer vision applications to natural language processing tasks, where I have demonstrated a keen eye for detail and a strong understanding of data labeling best practices. Additionally, my ability to adapt to new tools and technologies, coupled with effective communication skills, enables me to collaborate seamlessly with multidisciplinary teams and deliver exceptional results in AI model training.

Labeling Experience

Data Labeling Expert

Aws SagemakerVideoBounding BoxText Summarization

Identification and Annotation of Safety Hazards: Data labeling tasks would include identifying potential safety hazards within the supply chain environment, such as moving machinery, hazardous materials, obstructed pathways, and improper storage of goods. Each hazard would need to be accurately annotated to enable the platform to recognize and mitigate risks effectively. Object Detection and Recognition: Another crucial task is annotating objects and equipment within the site, including forklifts, conveyor belts, pallets, and loading docks. This involves labeling these objects to train the platform's computer vision algorithms to detect and recognize them in real-time, thereby facilitating proactive safety measures and interventions.

Identification and Annotation of Safety Hazards: Data labeling tasks would include identifying potential safety hazards within the supply chain environment, such as moving machinery, hazardous materials, obstructed pathways, and improper storage of goods. Each hazard would need to be accurately annotated to enable the platform to recognize and mitigate risks effectively. Object Detection and Recognition: Another crucial task is annotating objects and equipment within the site, including forklifts, conveyor belts, pallets, and loading docks. This involves labeling these objects to train the platform's computer vision algorithms to detect and recognize them in real-time, thereby facilitating proactive safety measures and interventions.

2021 - 2023

Education

Work History