I will do manual data labeling and annotation for ai ml
About this Gig
Are you looking for accurate and reliable manual data labeling for your AI/ML project? I can help!
I provide careful, manual data labeling and annotation services for text and image datasets, ensuring your machine learning models get clean, high-quality training data.
What I offer:
- Manual text annotation (sentiment tagging, categorization, entity labeling)
- Manual image tagging (object labeling, simple bounding boxes)
- Consistent labeling following your exact guidelines
- Careful quality checks before delivery
Why choose me:
- High attention to detail on every task
- Clear communication throughout the order
- On-time delivery as per the agreed package
- Willingness to make revisions if guidelines are followed but adjustments are needed
How it works:
- Share your dataset and labeling guidelines
- I manually label/annotate the items as instructed
- I review my work for accuracy before delivery
- You receive a clean, properly labeled dataset
Whether you're training a machine learning model, building a chatbot, or working on a computer vision project, I'll make sure your data is labeled accurately and on time.
Message me before ordering if you have a custom requirement or large dataset happy to discuss.
Technique:
Manual
Tagging type:
Text
•
Image
FAQ
What file formats do you accept for data?
I can work with CSV, Excel, or plain text files for text annotation, and common image formats (JPG, PNG) for image tagging.
Do I need to provide detailed labeling guidelines?
Yes, please share clear instructions or examples of how you want the data labeled. This ensures accuracy and reduces the need for revisions.
Can you handle large datasets beyond the package limit?
Yes, just message me before ordering and I can adjust the package or add extra items to fit your dataset size.
What if I need changes after delivery?
Each package includes revisions — I'll make adjustments based on your original guidelines at no extra cost within the included revision limit.

